Instana Blog

Author: Kevin Crawley

The Reality of Observability - Tuning Out the Noise
Thought Leadership
Many tools claim to offer Observability, through a combination of metrics, logs, and/or traces. But they all miss out on the real truth of observability - can you react and understand your application
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Scaling Microservices: Understanding Performance and Observability
Conceptual, Thought Leadership
Kubernetes has accelerated the complexity of software development. The industry needs observerability to manage these emerging systems.
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Docker vs Kubernetes: The Complete Guide
Conceptual, Thought Leadership
Docker vs Kubernetes: Is Docker dead? Can you still use Docker Swarm or should you jump straight to Kubernetes? Find the best solution.
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Instana Changes Performance Monitoring Again with SmartAlerts™ - the First Curated Alerting System That Includes Systematic Context
Announcement, Product
SmartAlerts, Instana’s revolutionary new approach to alert management, makes the alerting process effortless, intuitive and intelligent.
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Announcement, Product
Instana introduces sourcemaps for EUM, helping Javascript developers locate and understand the source of web application errors.
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Scaling Microservices – Understanding and Implementing Cache
Thought Leadership
Learn how the proper caching strategy and implementation can help create more scalable and robust microservice applications. #6 in our blog series on scaling microservice applications.
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Collecting Custom Micrometer metrics has never been easier
Developer, Thought Leadership
Learn how effortless it is to detect and collect your custom Micrometer telemetry metrics and include them in Instana's automated Application Performance Management (APM) solution, including automatic
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Scaling Microservices: Advanced Approaches with the AKF Scaling Cube
Announcement
Instana's Microservice Application Scaling series continues with an examination of the AKF Cube - an interesting framework to measure and improve scalability
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Scaling Microservices Cloud Burst
Developer, Thought Leadership
Scaling distributed systems is hard. In this post we'll discuss why the initial approach should always be optimization over replication.
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