Deployment Verification — Observability

Organizations ensure quality through software verification. To test a software component or system, organizations should ensure that services are installed, configured, and run in their intended test environments. Verification also involves ensuring that services perform their functions within an acceptable time, respond to inputs, and achieve a general result.

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What is APM?

APM stands for Application Performance Management. APM tools such as AppDynamics, Datadog, and Dynatrace enable organizations to keep track of application performance and monitor for regression.

How does Harness use APM?

Harness leverages APM Platforms and other markers to determine deployment health. A more complex task such as verifying and validating a canary deployment for promotion is handled in an automated fashion.

Curated Content

Learn why performance monitoring is critical, and how Harness leverages APM and machine learning to for its CI/CD pipelines.

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This blog post goes over the two key reasons to use a Application Performance Monitoring (APM) solution from a data science perspective, and how Harness leverages APM in its 24/7 Service Guard solution. 

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What’s the goal of Application Performance Management in software delivery? This blog post describes why eyes are turned towards OpenTelemetry given their influence in the APM solution space.

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What is Observability?

Observability is the measure of how well internal states of a system can be inferred from the knowledge of the external outputs.

How does Harness use Observability?

Harness leverages Observability Platforms and other markers to determine deployment health. A more complex task such as verifying and validating a canary deployment for promotion is handled in an automated fashion.

Curated Content

A CI/CD Evangelist presents an overview of Observability for Verification and a summary of how to scale efficient pipelines. Learn how customers use the Harness platform to deliver 80% faster and more securely.

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What is observability, and how are APM solutions solving the challenges of observability for modern enterprise applications? Learn more on why observability matters more and more in software delivery. 

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Observability leverages metrics, tracing, and logging capabilities to allow teams to better understand how their services interact/perform. Learn about how observability is playing a bigger role in Progressive Delivery, and about the latest trends in CI/CD.

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What are Accelerate Metrics?

The book Accelerate by Nicole Forsgren, Jez Humble, and Gene Kim has four key metrics to measure software team performance. Deployment frequency, lead time for changes, mean time to restore [MTTR], and change failure rate are the four key metrics mentioned.

How Harness uses Accelerate Metrics?

Harness has the ability to show Accelerate Metrics as part of its dashboard capabilities.

Curated Content

Harness Continuous Insights, an addition to our Continuous Delivery Platform, allows DevOps teams/leaders to measure software delivery performance using accelerate metrics. See it in action in this blog post.

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Learn why delivery metrics matter in the context of Site Reliability Engineering, and how innovating and delivering feature quickly can go hand-in-hand with SRE.

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Metrics-based process mapping (MBPM) can be used to improve your software delivery; this piece goes over all the steps of MBPM, and how metrics can improve effort and accuracy in delivery.

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What are Performance Gates?

Gates in software delivery are some sort of criteria that you have to pass before proceeding. Performance gates are designed to ensure that performance expectations, e.g. SLAs/SLOs, are met before fully being deployed into production.

How Harness uses performance gates.

Performance gates can be before, during, or after a deployment. Performance gates can be crucial for making judgment calls if a deployment is going to be or being successful. Harness has native integrations with several APM and Observability tools along with internal markers to determine health.

Curated Content

With the container and microservices bloom, we deal with larger and larger distributed systems. The topologies continue to grow as we bake in redundancy and performance SLAs.

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