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There was a time not too long ago, before the cloud was a part of every enterprise technology conversation, when integration work was considered the purview of a specific architecture and engineering group.

If messages failed to send, or services failed to respond, application stakeholders would create a trouble ticket for the integration team to address.

In some ways, this separation of labor was effective enough at the time. There were a finite number of point-to-point integrations between systems, and most request/response traffic would flow through an integration backbone, such as an ESB or MQ server.

Even if a developer did some of the adaptation work in their own code, when their applications would be promoted, it would be standard practice to hand over the specifications and allow integration teams to manage how the transactions would play out, with jobs and traffic scheduling to hopefully avoid bottlenecks.

Whenever a blockage did occur, integration engineers would be first on the scene, because they were the most familiar with how their team set up each adapter and data transformation step branching off of that message bus.

In the modern application world, integration has become way too complex to be the purview of one group, or even one huge department, as our applications now surf on an ever-changing sea of services and hybrid IT architecture that is connected to partners, and the world at large.

Covering complexity with MESH

The software development community at large constantly invents new ways to bridge the divide between message queues and point-to-point integrations in order to talk to disparate systems. There were web services and SOA, then various shades of integration fabrics, and then containers and service meshes as today’s cloud native architectures evolved.

One company attempting to tackle today’s integration challenges, meshIQ, has coined a new acronym to break down the integration pattern. In this case, it’s not another service mesh—MESH stands for “Messaging, Event processing, and Streaming, across Hybrid cloud.”

Separately, each letter in the MESH represents a broad technology category. The plan is to bring together a flexible solution to integrate distributed and decentralized technologies. MESH in this sense is just as much a thing you do, as a particular solution you would buy, because it changes the relationships of DevOps, architecture, and operations teams to the integration process.

New stakeholders for integration work with MESH

Gone are the days of throwing adaptation requirements and service tickets ‘over the wall’ to someone else.

Today, the old organizational silo of an integration team is giving way to a platform engineering function. Platform engineering is done by a federated team, perhaps drawn from a council of other stakeholder departments, combining solutions from selected vendors to provide developers, architects and other roles with the self-service tools they need to do development, deployment, and integration themselves, with minimal support or intrusion.

The advantage of providing a MESH for platform engineering is immediately obvious to any teams that previously had to wait for provisioning budget reviews and change control boards. We want to distribute integration work, and observability into the state of integration, down to new stakeholders in order to deliver new functionality faster, and respond to problems with faster remediation.

In this story, we’ll discuss five unique new stakeholders for MESH that benefit from this sea-change in integration roles and responsibilities.

Shared Services / Platform Teams

Shared Services groups are the most likely owners of the platform engineering initiative. Often, this group inherits some of the workload left behind by the departure of the old centralized middleware integration team, with a notable exception. Rather than acting as a ‘service bureau’ for others, they lay the self-service infrastructure foundations for application delivery and operations tooling to serve other employee groups.

Primary considerations: Control and Governance

Since shared services is still responsible for the ongoing support of both legacy middleware integration layers and newer API and event-driven hybrid cloud architectures, they are looking to MESH to gain a single point of control over all middleware, investigate problems, and make changes to objects such as repairing a message queue or event bus when needed.

Shared Services manages the inventory of the integration architecture used for platform engineering activities, ensuring that all of the assets in play and connections are holding up under the workloads of other constituent teams, and updating or retiring assets when needed.

Enterprise Architects

Enterprise Architects (or EAs) view integration from a high level, but they also need to dig into the details. For any new project, they will establish a starting data schema or communication format, then visit the MESH to decide on group permissions, and set the standards for ongoing integration projects across the enterprise. Importantly, the perspectives of EAs should prevent technology sprawl and eliminate redundant or dead-end components as underlying cloud technologies keep changing.

Key considerations: Standardization and Consistency

EAs are always seeking higher levels of automation and reproducibility for Infrastructure-as-Code (IaC) recipes and scripts such as Ansible playbooks, which define the desired to-be state of each next release in relation to the integration standards they specify. In these situations, the MESH normalizes API interfaces across multiple clouds, middleware stacks and data services, so underlying application development teams can deliver their own part with consistency, without excessive redefinition or customization.

Application Owners

Application Owners may come from either development, or the sales or marketing side of the business. These individuals often own the P&L (profit & loss) responsibility for an application, gathering market demand signals and customer requirements while advancing the feature roadmap and ensuring that the application meets customer and regulatory demands. The scope, revenue targets and budget of the product influences integration choices.

Key Considerations: Auditability and Change Awareness

As software becomes more distributed and granularized into microservices, the number of service connections and API calls that comprise an application increases exponentially. The Application Owner would use MESH observability to keep track of all configuration changes made by developers and admins for every object within their customized application domain view.

Using this method, they can generate a full audit trail of all changes: who executed them and when, how they contribute to the completion of each targeted feature, and the relative success metrics and integration risk of each change on the production system.

Application Developers

Application Developers have a strong need to provision their own dev and test environments, so they can be agile and productive without provisioning bottlenecks, and deliver new functionality without worrying about the timing of production change windows.

Key considerations: Self-service provisioning and flexibility

Every bit of workflow code a developer writes for modern systems is highly dependent on component-level integration and messaging layers, therefore they need ready and functionally complete self-service environments for testing and promotion.

Developers want the permissions and empowerment to move forward using a MESH to create and consume REST-style or real-time async APIs on middleware objects, without having to wait for environment provisioning bottlenecks or lengthy change request/review cycles. A tightly granular set of access privileges to groups of objects allows them to safely work within their own application feature.

Devs can check in code without impacting the dependencies of adjacent development teams or the production system at large, while architects and managers can maintain control through system-wide monitoring and standardization of the integration object library.

Application Support

Application Support takes many different forms in an organization. There are customer-facing support teams that can resolve simple user error problems, while taking in feedback and error reports. Employee support can assist platform engineering with a help desk function that provides educational resources and keeps productivity high for all constituents of the MESH. Operations support teams need production monitoring and deeper observability into the root causes of failures and performance problems.

Key Considerations: Real-time Insight and Policy Management

Maintaining high service level objectives (SLOs) for any application stack only happens with complete real-time monitoring, early awareness and alerting of issues. Given the complexity of underlying integrations, the MESH needs to provide machine-learning based filtering routines for runtime metrics and event data that is coming in too fast for a human to process.

To stay ahead of the rate of change and focus on what is significant, support teams can group together and classify analytics and targeted searches of source data in the MESH event catalog, and create monitoring policies that address the most likely risk factors for system instability, performance hits and potential security exploits. When a high-priority alert is received, support teams can then turn over the issue to the owner of the affected application domain or integration object, with an incident report for faster remediation.

The Intellyx Take

Organizations that are seeking to close the chapter of dedicated integration teams, and the inflexibly rigid provisioning and change management standards that accompanied them, should consider moving toward a modern integration MESH platform approach like meshIQ.

As the future of enterprise software integration will only become more distributed and fragmented across hybrid cloud resources, APIs and data services, so should our stakeholder roles and responsibilities change to meet the challenges of increased complexity in deployment.

©2023 Intellyx LLC. Intellyx is editorially responsible for this document. No AI bots were used to write this content. At the time of writing, meshIQ is an Intellyx customer. Image sources: TBA; Screenshot: meshIQ dashboard (optional)

Distributed transaction tracing (DTT) is a way of following the progress of message requests as they permeate through distributed cloud environments. Tracing the transactions as they make their way through many different layers of the application stack, such as from Kafka to ActiveMQ to MQ or any similar platform, is achieved by tagging the message request with a unique identifier that allows it to be followed.

For ease of understanding, it is similar to using an Apple Airtag or any similar GPS tracker to keep an eye on the progress of your luggage at the airport. This enables you to understand where it is at any particular point and observe the progress in real-time. Distributed transaction tracing is indispensable if clarity and observability are essential to you and your business.

Transaction tracing is crucial in today’s increasingly complex business landscape, where companies depend on numerous interconnected systems for operations and decision-making. It helps firms identify and resolve issues faster, improving performance, reliability, and customer satisfaction. However, with the shift from hybrid or standalone systems towards distributed, cloud-based architectures, tracing transactions across different systems and components is becoming much more challenging. We will explore how Integration MESH can deliver distributed transaction tracing capabilities, enabling companies to gain complete visibility into their middleware systems. 

Delivering Distributed Transaction Tracing Across Integration MESH

What is MESH?

MESH is an acronym for Messaging, Event Processing, and Streaming Across Hybrid Cloud. This is more than just middleware. It is an evolution beyond that and has become the nervous system that controls the entirety of the digital enterprise, whether on-site, hybrid or cloud. MESH has evolved from messaging to event processing to data streaming. These all still exist and have to be managed interoperably across the wide gamut of on-site, hybrid and cloud solutions deployed by businesses worldwide. This is where MESH comes into play.

An Integration MESH is a network of interconnected services and APIs facilitating communication between applications or microservices. It enables the components of a distributed system to interact as seamlessly as possible. It provides a distributed architecture that allows the business to scale and evolve faster.

Delivering Distributed Transaction Tracing Across Integration MESH

What is Distributed Transaction Tracing?

Distributed transaction tracing (DTT) tracks a transaction from start to finish across multiple services and APIs. It helps to analyze the system’s performance as a whole rather than on a component-by-component basis. DTT provides visibility into transaction flows, which, in turn, helps identify issues that can cause slow performance or system crashes.

You can follow a single event throughout its journey, as it travels through the application stack such as Kafka to ActiveMQ to MQ or any similar platform, and get a holistic view of the message flow from the beginning to its destination. This can often be delivered using the OpenTelemetry standard in conjunction with the meshIQ platform.  

Real-Time Insights

One key feature of Integration MESH that enables distributed transaction tracing is its ability to provide real-time insights into transactions. It does this by leveraging different protocols and technologies to capture and combine transaction data from disparate sources. This way, companies can get an accurate and up-to-date view of transaction flows and statuses across different systems. Furthermore, this capability extends beyond simple visibility to transaction monitoring, analysis, and management.

Centralized Governance and Control

Integration MESH also enables distributed transaction tracing by providing centralized management and control. This is made possible by the platform’s ability to manage integrations from a central location, with granular visibility and control over individual transactions as they flow from Kafka to ActiveMQ to MQ or any similar platform. This way, companies can identify issues quickly, pinpoint the root cause, and resolve them promptly. Furthermore, this centralized approach offers better security, compliance, and governance, by managing data privacy and access across different systems.

How can meshIQ help deliver DTT?

meshIQ provides a data-driven approach to Distributed Transaction Tracing that is flexible and scalable enough to meet the demands of even the largest and most complex IT ecosystems. The meshIQ analytics engine collects transaction data from various sources, including logs, metrics, and traces, and uses it to identify patterns and anomalies across different services. The detailed dashboards and visualizations generate alerts and notifications that help DevOps teams to address problems before they escalate.

Benefits of using meshIQ for DTT

1) Enhanced visibility: meshIQ’s detailed dashboards and visualizations provide a complete view of the transaction, reducing the time to identify and fix issues. The single pane of glass solution allows you to observe the entirety of the message journey throughout the diverse systems that comprise the ecosystem.

For many businesses, their message journeys are basically inside a black box that they are unable to see inside, and meshIQ is a market leader in the realm of observability.

2) Improved governance and collaboration: meshIQ fosters collaboration between teams through unique role-based access controls, which gives each team member the right level of access to the data they need. This guarantees that the correct permissions are assigned to those who need them and ensures good governance.

3) Automatic correlation and analytics: meshIQ’s analytics engine automatically correlates transaction data from multiple sources, which speeds up troubleshooting and problem-solving.  Pattern matching and machine learning can come into play to help identify potential problems or anomalies before they arise.

4) Scalable and flexible: meshIQ’s data-driven approach to distributed transaction tracing is robust, scalable, and can handle the largest and most complex IT ecosystems. There is such a wide variety of software that is being used in the middleware messaging space, and much of it is older, legacy software. The scalability and flexibility offered by meshIQ allows for reliable integration across the diverse range of available software solutions.  


In conclusion, distributed transaction tracing is critical for companies looking to improve their system performance, reliability, and customer satisfaction. MESH is a platform that can deliver these capabilities by providing end-to-end visibility, standardization, centralized management, and a high degree of control. Moreover, the platform’s ability to connect different systems and applications across complex and distributed architectures offers companies a holistic approach to integration and transaction management.

Join us for our biweekly TechTalk Tuesday series to learn more about our platform or contact us to find more.

In today’s rapidly evolving technological and business landscapes, staying competitive requires more than just a great product or service. It demands a technological edge that can drive efficiency, innovation, and overall growth. This is where partnering comes into play – it’s like turbocharging your business engine. Today, meshIQ is looking to turbocharge our sales teams, processes, and reach by adding power via partnerships.

Unleashing Technological Horsepower

Like a turbocharger dramatically enhances an engine’s performance, partnering with Resellers and Services partners can rapidly scale our business operations. These tech-savvy collaborators bring in-depth expertise, cutting-edge technology, and a fresh perspective to the table. This boost of digital power will drive our business to new heights.

1. Expertise Injection

Resellers and System Integrators are masters of their craft. Their teams consist of skilled professionals who specialize in various areas of selling software and everything from design to support and project management. By partnering with them, we are aiming to tap into a wealth of knowledge that would be challenging, costly, and above all time-consuming to develop in-house.

2. Accelerated Innovation

In the same way that a turbocharger boosts an engine’s horsepower, a Partner can propel our business forward. They’re immersed in the latest industry trends, ensuring that mutual business stays relevant and adaptive. Their innovative solutions can catalyze new product development, streamline processes, and even open doors to entirely new markets and prospects.

3. Enhanced Efficiency

Just as a turbocharged engine optimizes fuel consumption, a Partner has the potential to streamline our business processes. By augmenting services and sales, their extended teams can save time, and scale our sales and complement our services teams.

4. Flexibility and Scalability

Turbochargers provide an extra boost when needed, and so do Partners. They offer flexible solutions that can be tailored to our customers’ unique needs. Plus, as the business expands, their sales reps and engineers can effortlessly accommodate increased demands, ensuring a smooth growth trajectory.

5. Cost-Effectiveness

While turbocharged engines may consume more fuel, partnering with a Reseller or System Integrator can actually save costs in the long run. Investing in partnerships fosters customer trust, reduces operational inefficiencies, and leads to new sales opportunities. The return on investment becomes evident as our business becomes leaner, more efficient, and more profitable.

6. Focus on Core Competencies

Just as a turbocharged engine specializes in generating power, meshIQ needs to add power to our existing sales teams. By delegating the complexities of selling and services to external experts, we can concentrate on prospecting and product development. This division of labor fosters a more streamlined and productive operation.

Final Thoughts

The rapid acceleration in innovation, efficiency, and sales growth potential can be a game-changer. As we consider our company’s future, we are mindful of how powerful partnerships can be the key to outpacing the competition and reaching new heights.

So, why wait? Buckle up and prepare for the ride of being a premier Partner of meshIQ. Just as a turbocharged engine transforms an ordinary vehicle into a high-performance machine, your partnership with Us could revolutionize customer outcomes.

Remember, every successful partnership begins with a conversation. Reach out to us and let’s explore the capabilities and how we can fuel our customer’s journey into the fast lane of success.

Most companies in today’s business landscape that deal with large amounts of data want to integrate their applications so that they can pass data between them seamlessly and easily. Being able to ensure that you can see exactly what is happening at every stage of the process is key, and this is where approaching the process with observability in mind can make a real difference.

Deciding at the outset that observability is something that you want to be baked into the process means that you can plan and execute with that in mind. One of the easiest ways to do this is to use meshIQ, which is an observability platform for Messaging, Event Processing, and Streaming Across Hybrid Cloud (MESH).

What Kind of Applications Need Integration?

An excellent example of the kinds of applications that need integration to work together is e-commerce platforms which need to connect to customer relationship management applications, stock management and order fulfilment applications. These can all require there to be fluid movement of data between the different databases that hold the relevant information at each step of the process.

There are different types of application integration, and at their most basic level, some of these can be point-to-point, where integration is established directly between two different applications in order that they are able to communicate with each other. In cases such as this, there are numerous problems, and these include a lack of scalability and resistance to change. If you need to hand code every new integration, the deployment and testing times for any upgrades can prove to be inefficient in the extreme and unsustainable in the longer term.

A slightly more advanced way of allowing integrations is to incorporate hub and spoke or enterprise bus architectures. Both are now considered to be legacy systems. Still, the idea behind them was that it was easy to add another integration to the system as it just needed to connect to one spoke of the “wheel” to integrate with all the other applications that were already integrated. These architectures tend to be described as middleware solutions, and they are typically deployed in on-premises solutions, which is a large part of why they are considered legacy systems today, as cloud-based systems have become the norm.

With this shift en-masse to the cloud, what we are seeing is a migration to Integration Platform as a Service (iPaaS) which is the modern method of integrating application solutions which includes an impressive array of additional features, including complete cloud-based data integration, data management functions and easy connections to APIs. These systems are set up to be able to offer immense versatility in what they can integrate, encompassing on-premises applications as well as those which are cloud-based.

The beauty of using a cloud-based system such as meshIQ is that it is a streamlined process which accounts for and tracks all the data throughput of the system and can locate individual pieces of data within the system with a high degree of accuracy.

Why Do We Need Application Integration?

Application integration is important to ensure that data redundancy isn’t taking up excessive storage space and slowing down the system. It also ensures that there is no confusion generated by having multiple copies of the same data and it not being clear which should take precedence. In essence, different applications can create their own data silos when this happens, which defeats the whole idea and purpose of integration between them. Data inconsistencies can cause problems further down the line and can require human intervention to rectify any problems that occur.

Increased Productivity

Being freed from the chore of having to create point-to-point connections between different applications will allow your employees to use their time more productively to further the aims of your business, using the information gleaned from your data.

Easy Scalability

The APIs and connectors that are available to be utilized can make it so much easier to scale up solutions and add connections where needed without having to create bespoke connections by hand.


This is one of the critical considerations in any business, and yours is no different. The savings in terms of efficiency make modern ways of application integration a necessity in the current economic climate. To run a successful business, they are simply a must.

Why is Observability so Important?

Observability is vital so that you can see exactly what is going on throughout your system at any given moment. Being able to accurately track and trace data wherever it happens to be in your platform is necessary to safeguard the viability of your business. Knowing the status of your data at any given moment is made easier through the building in of observability solutions from the ground up.

This is where meshIQ comes in. meshIQ’s proprietary application integration solutions allow a single pane of glass observability solution that can pinpoint everything that is happening in the system and can allow you to shine a light into the inner workings of your system, finding the cause of Irregular Operations (IROPS) and reducing the Mean Time to Repair (MTTR) significantly in the process.

Many solutions treat observability as an afterthought, but it is treated as a top priority by meshIQ because it is understood that time is money and that if your system is down, then you are losing money that whole time. With some other systems, looking for where there is an outage can be like looking for a needle in a haystack but with the observability that is built in with meshIQ, you can immediately pinpoint where the problem is and take steps to rectify it.

You can even set rules so that if the same problem occurs in the future, it is automatically dealt with in a particular way, which can actually mean that it is never such a significant problem in the future as it is automatically dealt with.

Join us for our biweekly TechTalk Tuesday series to learn more about our platform or contact us to find more.

When businesses look at how best to understand the performance levels of their platforms, some of the best incident management metrics to look at are Mean Time Between Failures (MTBF) and Mean Time To Resolution (MTTR). These two measurements will give an excellent indication of the health and speed of the system, as well as the ability of the platform to take care of any anomalies that have been detected or to flag them up for others to take action to resolve them.

By understanding these measurements, it is possible to gain a better insight into how reliable and responsive their platform is. Additionally, they can help identify any weak points in the system or areas where issues may need to be addressed quickly. With this knowledge, companies can then take all appropriate action to ensure that their platforms continue running at optimal levels with minimal disruption.

Fine grained observability of your system will obviously make it easier to pinpoint exactly where some of the problems are taking place and help reduce the amount of time that it takes to respond to any incidents. We will take a closer look at how meshIQ delivers fine grained observability to do this shortly.

Mean Time Between Failures – MTBF

Mean Time Between Failures is a measure of reliability that logs the uptime that the system has experienced between failure events. It is a rolling mean that is calculated every time there is another failure so that it is possible to log this and use it as a metric to say whether the platform is trending toward better or worse MTBF.

This can be a useful way of evaluating any changes that have been made because the historical record of the MTBF can be reviewed in the light of any changes made to the platform. If instability has been introduced at any stage then it will be obvious at which point this happened because of the negative change that it will make to the MTBF figures.

Mean Time Between Failures (MTBF) is a key indicator of the reliability of a system, and it can be used to identify potential problem areas that needs improvement. By understanding MTBF, organizations can make informed decisions about how best to improve their systems’ performance and uptime.

It also provides an indication of how well components are performing in comparison to each other, as well as providing useful insights into the overall health of the system. With this information at hand, teams can develop strategies for reducing downtime and increasing system efficiency.

How to Calculate MTBF

The value of the MTBF can be determined by multiplying the operating time of a repairable machine or apparatus by the number of failure observations in a specific time period. Calculations can be made using multiple failures related to products or failures related to multiple products. The time of the failure is the total hour of operation and the total failure. Total operational time is the total period of an application product that was not incidental during the time you are looking at analyzing. Total failure of the product is the total failed product in a given period.

The Importance and Usefulness of Mean Time To Resolution

MTTR helps organizations detect and eliminate inefficiency, which results in increased downtime and therefore poor productivity and loss of profits. MTTR is used by business owners to analyze and implement their strategy, and calculate how long it takes for systems to be fully operational again.

It is important to the company’s bottom line to figure out how to take action that eliminates or vastly reduces the downtime associated with Irregular Operations (IROPS). Getting the system back up and running and on an even keel after an incident is a matter of priority as any unplanned downtime can cost both money and client confidence. 

What is the difference between MTTR and MTBF?

MTBF is an indicator of the rate of breakdown. After a breakdown, the MTTR describes what can occur immediately. Although the data may vary, they can be used together in analyzing systems uptime. The most beneficial result will be the steady decrease in MTTR and increase in MTBF, and describes a system with minimal downtime and the ability to rapidly recuperate if something happened at all.

MTBF and MTTR are two measurements used to analyze the reliability of a system. The Mean Time Between Failure (MTBF) is an indicator of how long a system can be expected to run without any major problems or breakdowns happening. The Mean Time To Resolution (MTTR) measures the speed that the system can be restored after a failure or breakdown has occurred.

By combining these two metrics, businesses can get an understanding of their systems’ uptime and determine what areas need improvement in order to increase efficiency and reduce downtime.

How Can Increased Observability Improve MTTR and MTBF?

meshIQ is an observability platform that has been designed from the ground up in order to offer increased visibility into complex integration middleware infrastructure namely Messaging, Event Processing, and Streaming platforms deployed across Hybrid Cloud (MESH) platforms and allow for 360-degree situational awareness.

The capabilities inherent in the meshIQ system mean that unlike other methods that offer observability solutions for MESH platforms, they can pinpoint where any points of failure occur far more accurately. A good analogy would be that of a sports stadium. Some of the most similar offerings would be able to spot where there was an irregular operation and trace it to a section of stadium seating, whereas meshIQ would be able to pinpoint the actual seat.

In order to rectify any problem, you have to know what is happening and where in the system it is located before taking remedial action. The high quality, single pane of glass observability offered by meshIQ means that they can find the point of failure far more quickly and also monitor the platform constantly for any signs of decreased performance, therefore improving both the Mean Time to Recovery and Mean Time Between Failures across the full stack and the entirety of the distributed platform.

In a nutshell

  1. Majority of the application problems stem from the underlying middleware layer whether it’s a slowdown or an outage. meshIQ detects them quickly and prevents an outage.
  2. Incorrect configurations can cause problems when a new build is deployed, meshIQ enables quick rollback across the whole middleware stack.
  3. meshIQ supports all major middleware platfiorms. Which means it can find that ‘needle in the haystack’ problem navigating the maze of middleware connections.

Ultimately, using meshIQ technology allows for teams to utilize their processes and procedures in an automated way to significantly reduce the MTBF and MTTR within their organizations.

Join us for our biweekly TechTalk Tuesday series to learn more about our platform or contact us to find more.

The last decade has been nothing but a roller coaster ride for the airline industry. The pandemic has transformed it forever and now it needs to reevaluate its digital transformation priorities on how to manage traveler expectations. Taking it a step further, travelers buying behavior is changing farther as now they will want to book tickets while chatting with an AI interface.

The transformation was already underway. In 2020, Google Cloud and Sabre announced a partnership to modernize Sabre. Recently, American Airlines announced their modern rebooking app launched in partnership with IBM. Lufthansa announced industry’s first continuous pricing tailored to suit individual customer attributes.

Key goals from the Digital Transformation initiatives:

  1. Revenue Optimization
  2. Pricing/Dynamic Pricing
  3. Enhanced Customer Experience & Engagement
  4. Fleet modernization and Emissions reduction

To achieve these goals, airlines are already making investments and are expected to make significant investment in their IT infrastructure over the next few years as they recover from the pandemic and adopt newer technologies.

According to a recent airline industry insights report, IT investment reached $37B in 2022. The top three areas that airlines plan to bolster with IT development over the next few years include:

Cloud Computing – Scalability is a major issue for many airlines. From the customer facing website to internal apps, everything comes under strain during peak season and any delay due to weather etc. can cause an expensive meltdown. Scaling automatically using Cloud based infrastructure can lead to much smoother experience for airline staff and passengers.

Security – Safeguarding passenger and flight data is paramount along with the safety of the flight. With the tremendous risks posed by state-backed and private hacker groups around the world, it is crucial for airlines to invest in data security to safeguard stored data and enable secure integration with other airlines and government agencies.

Modernize Apps – As customer expectations evolve, Airlines have no option but to modernize their apps, providing features and enhancements that improve customer experience and loyalty.

All this is only achieved via modernization. Many of the systems used by airlines today are decades old and completely outdated. Airlines will continue to make investments into their IT landscapes to bring the technology used in the aviation industry up to the modern standards that are expected of businesses today and deliver more AI, facial recognition, Cloud based apps. All these modern applications also require modern Event driven architectures connecting these applications for better scalability and reliability.

Modern apps need better Observability

The older observability tools do not work for a few reasons.

Deliver Aviation excellence with meshIQ

At meshIQ, we specialize in monitoring Integration MESH and our observability platform is geared to monitor Messaging, Event Processing, Streaming infrastructures deployed across Hybrid cloud. We monitor mission critical MESH infrastructure that connects different aviation apps to each other over modern Integration patterns such as Event Driven Architectures. This results in higher reliability, and scalability of apps themselves reducing the risk of bottlenecks, slowdowns, and meltdowns during peak travel season.

Join us for our biweekly TechTalk Tuesday series to learn more about our platform or contact us to find more.

Apache Kafka has come a long way since its initial development at LinkedIn in 2010 and its release as an open-source project the following year. Over the past decade, it has grown from a humble messaging bus used to power internal applications into the world’s most popular streaming data platform. Its evolution is remarkable, and it has taken the industry by storm, quickly becoming a go-to solution for data streaming and processing.

Today, Apache Kafka is used by some of the most influential names in technology, from global corporations to small startups. This blog aims to provide insight into the evolution of Apache Kafka since 2010 and why it continues to be a popular choice for streaming data and the use cases where its preferred over traditional messaging platforms.

The Beginnings of Kafka

Apache Kafka was first developed in 2010 at LinkedIn as a distributed stream processing framework. At the time, the challenge was to address scalability for real-time data feeds, and the company’s initial data system was built on Apache™Hadoop®. As they began re-engineering their infrastructure, they realized that operationalizing and scaling the system required a considerable amount of work.

That led to the development of Kafka as a distributed system that could connect applications, data systems, and organizations for real-time data flow. This goal has since been achieved, leading to Kafka’s current status as an industry-leading messaging middleware platform.

Apache Kafka has grown in popularity and is now an integral part of many companies’ data streaming infrastructure. With its scalability, reliability, and robustness, Kafka has enabled businesses to streamline their data processing operations and reliably transport large volumes of data across applications.

The Evolution of Kafka’s Features Over Time

Apache Kafka’s features have evolved over an extended time period, allowing it to adapt to the changing needs of businesses and developers. The platform has become more secure, reliable and efficient, as well as offering new features such as stream processing and data governance.

Kafka Connect has also been introduced, making it easier for organizations to integrate their data sources with the platform. Furthermore, Kafka’s cloud-native architecture has allowed organizations to take advantage of managed services and abstract away the operational efforts associated with running a distributed system. All these features have enabled Apache Kafka to become the leading messaging middleware platform it is today.

Solutions for Kafka Monitoring

As Apache Kafka has evolved to support mission critical use cases, the monitoring and observability needs have grown as well. meshIQ’s Navigator delivers observability and management into Apache Kafka. It provides a single pane of glass observability of all Kafka instances, spanning clusters, topics, brokers and more.

Users can drill down into the data to to see in real-time exactly what is going on within the Kafka cluster. There are also out-of-the-box alerting capabilities, so it is easy for the developers to understand where any potential problem may be coming from and what can they do to prevent that problem from causing a production outage.

Apache Kafka vs IBM App Connect Enterprise vs IBM MQ

Apache Kafka was developed at around the same time as several other prominent middleware stack and Message Queuing applications, including IBM App Connect Enterprise (ACE) and IBM Message Queuing. It is, therefore, unsurprising that these are some of the major players in the messaging middleware space today.

Most comparisons of the features in each of the solutions tend to come out reasonably even across the board, with some users preferring the no-coding approach taken by IBM ACE to that of Apache Kafka. Having said that, others praise the safety and security of Apache’s cluster and the relief of knowing that if one node fails, other nodes will seamlessly take its place with no interruptions to services.

Apache Kafka is considered to be significantly faster than IBM MQ, so this is advantageous in an environment where message delivery speed is of the essence. Apache Kafka also scales well across a distributed environment and is optimized for this use case. It also delivers large scale data replication via Mirrormaker (and new Replicator) where data is continuously replicated in a geographically distant location for backup or failover.

All of these systems are of exceptionally high quality, with reviews by industry professionals consistently putting each solution at somewhere near four and a half out of five stars. This means you can be sure that whichever you choose for your business, you are purchasing a messaging middleware solution that has been tried and tested rigorously in the field and is being consistently improved upon with each new iteration.

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Earlier this month, we announced a rebrand to meshIQ and in this blog we will highlight the reasons behind the rebrand and what you can expect going forward.

Where We Have Come From

Nastel has been at the forefront of some major technological innovations in the middleware messaging management sphere. We have been managing complex enterprise-level application stacks and providing single-pane-of-glass monitoring, alerting and analytic tools that allowed businesses to understand what was happening to messages deep inside their message queues and brokers. Nastel has simplified how businesses interact with their messaging middleware, with sophisticated tools reporting and visualizing what was once unreadable machine data in ways that allow for smarter business decision-making in real-time.

Where We are Going

As meshIQ, we are looking to build on our illustrious past and move on to the next stage in our evolution as a company and deliver solutions for broader messaging needs. Our new name signifies our expanded focus on broader Integration MESH.

MESH stands for Messaging, Event Processing, and Streaming infrastructures deployed across Hybrid-cloud.

Messages follow a pre-configured path, using queueing technologies like IBM MQ, MSMQ etc.

Events are broadcast using a pub/sub model. A broker usually routes the events to destination.

Streaming technologies like Kafka deliver high speed data streams using persisted data.

Hybrid is essentially where these platforms are hosted on-premises, Cloud or both.

IQ points to the fact that this is the smartest way businesses can handle all their data streaming and messaging infrastructure management in one place. Our purpose-built single-pane-of-glass architecture allows for full observability of the integration MESH.

On Becoming meshIQ

Taking Aim at the Future

Sometimes you have to aim big to make the kind of impact that you would like, and this is something that we have never been afraid to do at Nastel Technologies. In the next evolution of our company, we are looking to “cross the chasm” between the expectations of DevOps professionals and the current generation of Application Performance Management systems on the market.

We aim to solve the most significant problems faced in the industry today with the same vigor and verve that has always been associated with our company.

In the last decade, the complexity of Integration platforms has increased, and DevOps professionals need a solution to manage and deploy complex configurations when building apps that use Messaging, Event Processing or Streaming technologies. Additionally, they want the ability to observe the performance of their app and rollback configurations if needed.

Ideally, they want a single pane of glass to manage and monitor the complex M/E/S landscape and speed up the Mean-Time-To-Resolution (MTTR) to better deliver on Service Level Agreements (SLAs) and improve the overall user experience. 

What Does meshIQ Look Like?

Data is the backbone of any enterprise, and the messaging and streaming technologies form the central nervous system enabling apps and platforms critical for IT and the business. With the meshIQ platform, we are proud to be able to offer what we would describe as “observability platform for an organization’s digital nervous system”.

This platform will deliver DevOps, monitoring, management, and intelligence for the MESH.

Many vendors treat integration infrastructure like a black box, whereas we offer unparalleled observability and governance oversight. We complement APM platforms by delivering visibility and management of the black box.

What’s Next?

If you are an existing customer, our products will continue to work as you have known them. As you use our support apps and documentation, you will notice the new brand and new URLs. Over the next several months, we will have some exciting announcements in the following two areas.

So, stay tuned.

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Integration is a fundamental part of any IT infrastructure. It allows organizations to connect different systems and applications together in order to share data and information. As organizations become more complex and interconnected, they need to ensure they have complete observability and monitoring of their integration architecture. This is essential in order to discover, understand and fix any issues that can arise. Nastel’s complete observability & monitoring of integration infrastructure gives 360° Situational Awareness®


The need for having a complete observability & monitoring of integration infrastructure solution has been driven by the increasing number of integration services, systems, architectures and applications being used by enterprises. It is now necessary to have a comprehensive view of the entire integration ecosystem to avoid issues with data availability, latency, reliability and performance.

Observability & Monitoring

Complete observability & monitoring of integration infrastructure is essential in order to ensure continuation of operations and prevention of system outages. It is important for organizations to be able to have visibility into the performance and reliability of their integration infrastructure. This requires a combination of tooling and practices, such as logging, metrics, tracing, alerting and visualization. Nastel Navigator provides visibility into the entire integration environment.


Logging is one of the most important aspects of observability & monitoring. Logs should be collected and stored in a centralized location. They should be clearly labeled and easily accessed. Logs can capture all the necessary information in order to properly track the performance of the infrastructure.


Metrics are essential in order to understand the performance of the integration infrastructure. Metrics are collected, stored and monitored in order to be able to analyze changes in the environment. Metrics should be collected from the applications and infrastructure in order to properly track performance.


Tracing is also essential for understanding the flow of data through the system. It is important for organizations to understand where data is being received, processed and stored. Traceability helps organizations identify and pinpoint any issues that may arise.


Alerts allow organizations to be notified of any issues with the integration infrastructure. Alerts should be configured to notify administrators of any changes in the environment, including changes in performance or reliability.

Nastel is honored to receive a total of 18 prominent badges across multiple categories as High Performers in the Winter 2023 report by G2.

G2 is the world’s largest and most trusted software review platform marketplace. More than 80 million people use G2 to make smarter software decisions based on authentic peer reviews. Quarterly, G2 highlights the top-rated solutions in the industry, as chosen by the source that matters most: our customers.

Nastel has been recognized with the following Winter 2023 awards:

Nastel was also voted #1 for the best support in MQ and Configuration Management for 2 quarters in a row (Fall and Winter).  This means that we had the highest support ranking than any product within that category in winter 2023. 

Voted #1 for Best Support (2 consecutive quarters)


High Performers

Nastel’s Highlighted Reviews

Here’s what recent customers had to say about Nastel this year:

Nastel provides leading-edge tools to improve the management and monitoring of key enterprise infrastructure products like IBM MQ and Kafka. Nastel is in a class of its own, no competitors’ products providing the level of value that Nastel provides

– Art R, Sr IT Solutions Architecture Consultant

I needed a new way to monitor the performance of the environment based on our middleware. I’ve been looking for a solution that would allow me to see a complete overview of the entire system and in a fast, accurate and efficient way Nastel has helped me achieve it. The integration with IBM MQ is very good and the truly powerful capabilities of their data management is a huge pro for Nastel Autopilot. Through this comprehensive ecosystem monitoring, We was able to provide detailed reports to directors and the investors, seamlessly and easily with the ability to move data across the platform is excellent.

– Abeer M, Lead Data Analyst

The Navigator tool is extremely powerful and provides great granularity of control for users. For admins it makes it very easy to manage these. I have not found any other tools which provide this level of access control.

– Paul M, Senior Middleware Engineer

We sincerely thank all of our customers for taking the time to share their valuable experiences with us on G2. As we strive to deliver the best products and services, your feedback is extremely important to us.

Our awards and the methodology placed behind it

G2 scores products and vendors based on reviews gathered from our user community, as well as data gathered from online sources and social networks. They apply a unique algorithm to this data to calculate the customer Satisfaction and Market Presence scores in real time.

To read additional reviews for yourself, check out Nastel on G2.

You can log into to dive into the Winter 2023 Reports here.