Scaling Kafka? Learn How To Avoid Costly Mistakes! Download Our Free eBook
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Published July 19, 2022

Nastel Recognized as Leader in Integration Infrastructure Management & Transaction Observability by GigaOm

meshIQ
By meshIQ

New Analyst Report Details Emerging i2M Sector, Market Landscape, and Key Insights for IT and Business-level Buyers

"Nastel is uniquely placed when it comes to understanding the configuration information and message content of messaging middleware and integration infrastructure”

— Saurabh Sharma, GigaOm

 

Nastel Technologies, the world’s #1 i2M (Integration Infrastructure Management) company, today announced that it has been rated as a leader in GigaOm’s new Integration Infrastructure Management & Transaction Observability Sonar Report.

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Nastel Recognized as Leader in Integration Infrastructure Management & Transaction Observability by GigaOm
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Published June 27, 2022

7 DevOps practices to improve application performance

meshIQ
By meshIQ

Devops is tough, but the choice between faster development and improving reliability shouldn't be. Consider shifting-left security, better observability, AIops platforms, and more.

Devops is primarily associated with the collaboration between developers and operations to improve the delivery and reliability of applications in production.

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7 devops practices to improve application performance
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Published February 25, 2022

Intelligent Machine Monitoring

Cathy Bernardone
By Cathy Bernardone

Artificial Intelligence (AI, also called Machine Learning) is certainly making its way in the world. Technologies such as Voice Recognition, Face Recognition, Predictive Analytics, Self-driving cars, and Robotics are now becoming embedded into our society. With the advent of big-data, these technologies can become more and more powerful and more and more a part of our everyday lives.

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Intelligent Machine Monitoring
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Published November 13, 2021

Nastel Releases i2-aware AIOps, Analytics & Tracking Platform for Complex Enterprises

By Steven Menges

XRay 1.4 Solution Plugs Data and Analytics Gaps for Enterprises to Enable Insights from the Integration Infrastructure (i2) Layer, IoT, and Containers.

Nastel Technologies, the leader in Integration Infrastructure Management (i2M) solutions for complex enterprises, today announced the immediate availability of the XRay AIOps and Tracing and Tracking solution's latest release.

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Nastel Releases i2-aware AIOps, Analytics & Tracking Platform for Complex Enterprises
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Published November 9, 2021

Observability, AIOps, APM, and i2M: The Partner Ecosystem for IBM MQ Enterprises

By Steven Menges

Complex enterprises have an integration infrastructure (i2) layer that connects technologies and applications across cloud, data center, virtualized systems, mainframe, edge computing, etc.

Integration Infrastructure Management (i2M) is the “management” of the i2 layer and includes:

  • Configuration and security management
  • Monitoring and fault management
  • Alerting and automation
  • Performance optimization

The i2 layer includes a core middleware application (such as IBM MQ) along with many other “integration” technologies, such as MFT (managed file transfer), IoT, REST APIs, DataPower Gateway, and other messaging technologies (i.e., Kafka, TIBCO EMS, IBM ACE, IBM Integration Bus (IIB) and more).

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Observability, AIOps, APM, and i2M: The Partner Ecosystem for IBM MQ Enterprises
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Published August 12, 2021

Was Cloud A Mistake?

meshIQ
By meshIQ

I just heard that businesses are repatriating cloud workloads.

I was told, “The history of IT is paved with dreams of lower costs, better performance, and higher reliability through migrations to new platforms and languages and new architectures and infrastructures.”

“Some of the biggest recorded IT waste has been when companies focus on the ‘next big thing’ and have issues achieving successful implementations.

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Was Cloud A Mistake?
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Published July 9, 2021

Life, the Universe and AIOps

meshIQ
By meshIQ

AIOps is an area of technology that is developing rapidly and is generally accepted to mean “using machine learning to contextualize large amounts of data”.

While data analytics systems are great at identifying unusual patterns in large amounts of data (for example in a data lake) they can be quite poor at providing context to the signals they detect.

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Life, the Universe and AIOps

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