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crazylion lee

GitHub - naver/pinpoint: Pinpoint is an open source APM (Application Performance Manage... - 0 views

github.com/pinpoint

java apm

shared by crazylion lee on 15 Mar 18 - No Cached
  • crazylion lee on 15 Mar 18
     
    "Pinpoint is an open source APM (Application Performance Management) tool for large-scale distributed systems written in Java. http://naver.github.io/pinpoint/"
crazylion lee

GitHub - dianping/cat: Central Application Tracking - 0 views

github.com/cat

apm

shared by crazylion lee on 15 Mar 18 - No Cached
  • crazylion lee on 15 Mar 18
     
    "Central Application Tracking"
crazylion lee

OpenZipkin · A distributed tracing system - 0 views

zipkin.io

java apm tracing

shared by crazylion lee on 12 Mar 18 - No Cached
  • crazylion lee on 12 Mar 18
     
    "Zipkin is a distributed tracing system. It helps gather timing data needed to troubleshoot latency problems in microservice architectures. It manages both the collection and lookup of this data. Zipkin's design is based on the Google Dapper paper."
張 旭

Intro to deployment strategies: blue-green, canary, and more - DEV Community - 0 views

dev.to/...blue-green-canary-and-more-3a3

devops deploy system micro service

shared by 張 旭 on 23 Nov 18 - No Cached
  • using a service-oriented architecture and microservices approach, developers can design a code base to be modular.
  • Modern applications are often distributed and cloud-based
  • different release cycles for different components
  • ...20 more annotations...
  • the abstraction of the infrastructure layer, which is now considered code. Deployment of a new application may require the deployment of new infrastructure code as well.
  • "big bang" deployments update whole or large parts of an application in one fell swoop.
  • Big bang deployments required the business to conduct extensive development and testing before release, often associated with the "waterfall model" of large sequential releases.
  • Rollbacks are often costly, time-consuming, or even impossible.
  • In a rolling deployment, an application’s new version gradually replaces the old one.
  • new and old versions will coexist without affecting functionality or user experience.
  • Each container is modified to download the latest image from the app vendor’s site.
  • two identical production environments work in parallel.
  • Once the testing results are successful, application traffic is routed from blue to green.
  • In a blue-green deployment, both systems use the same persistence layer or database back end.
  • You can use the primary database by blue for write operations and use the secondary by green for read operations.
  • Blue-green deployments rely on traffic routing.
  • long TTL values can delay these changes.
  • The main challenge of canary deployment is to devise a way to route some users to the new application.
  • Using an application logic to unlock new features to specific users and groups.
  • With CD, the CI-built code artifact is packaged and always ready to be deployed in one or more environments.
  • Use Build Automation tools to automate environment builds
  • Use configuration management tools
  • Enable automated rollbacks for deployments
  • An application performance monitoring (APM) tool can help your team monitor critical performance metrics including server response times after deployments.
crazylion lee

GitHub - pyroscope-io/pyroscope: - 0 views

github.com/...pyroscope

apm ruby golang python node

shared by crazylion lee on 23 Feb 21 - No Cached
  • crazylion lee on 23 Feb 21
     
    "Pyroscope is an open source continuous profiling platform. It will help you: "
張 旭

Using NGINX Logging for Application Performance Monitoring - 0 views

www.nginx.com/...ication-performance-monitoring

nginx performance log

shared by 張 旭 on 22 Sep 21 - No Cached
  • taking advantage of the flexibility of NGINX access logging is application performance monitoring (APM).
  • it’s simple to get detailed visibility into the performance of your applications by adding timing values to your code and passing them as response headers for inclusion in the NGINX access log.
  • $request_time – Full request time, starting when NGINX reads the first byte from the client and ending when NGINX sends the last byte of the response body
  • ...3 more annotations...
  • $upstream_response_time – Time between establishing a connection to an upstream server and receiving the last byte of the response body
  • capture timings in the application itself and include them as response headers, which NGINX then captures in its access log.
  • $upstream_header_time – Time between establishing a connection to an upstream server and receiving the first byte of the response header
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