Go is one of the most popular and most used languages in the world; known for its simplicity, speed, productivity, easy concurrency, ease of use, ease of reading and learning, static binaries, cross platform nature, amazing community etc.

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The Go programming language

Today in 2020, Go is used by at least 25% of the Fortune 100 companies like Walmart, Apple, Amazon, Alphabet/Google, Microsoft, American Express, JP Morgan Chase, Home Depot, Facebook, Walt Disney, Netflix, Paypal, and very many companies in the Fortune/Global 2000 and many globally. Very many prominent and popular cloud computing projects are built using Go e.g Kubernetes, Istio, Docker, Prometheus, Jaeger


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Groupcache * OpenCenus * Go

Distributed caching is a pervasive technique for scaling web services. Distributed caches help alleviate latency loads by allowing reuse of expensively produced data, because generation of new data is usually more expensive than lookups of the already generated data. Throughout the history of the internet, caching technologies like Memcached, Redis, Varnish etc have thrived and enabled web services to scale since data like images, static pages can be distributed to caches geographically closer to users and most of that data doesn’t change. …


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OpenCensus for instrumented Redis clients in Java and Go

In this post we’ll examine Redis clients instrumented with OpenCensus in Java and Go, and apply them directly to use Redis in a media search service to alleviate costs, throttling, load, bandwidth and overall monetary expenses for a product.

TL;DR: We are excited to announce that we’ve instrumented some popular Redis clients in Java and Go for both tracing and metrics. The instrumented Redis clients are:

Jedis in Java: https://github.com/orijtech/jedis/pull/1

Gomodule/redis in Go: https://github.com/orijtech/redigo/pull/1

Go-redis/redis in Go: https://github.com/orijtech/redis/pull/1

You can see more of some of the integrations that we are rolling out at https://opencensus.orijtech.com


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OpenCensus for Python gRPC developers!

In this tutorial, we’ll examine how to use OpenCensus in your gRPC projects in the Python programming language to give observability insights into your server! We’ll integrate with OpenCensus exporters for the Jaeger, Stackdriver Tracing and Monitoring backends to help dig through and alleviate problems on your backend.

gRPC is a modern high performance framework for making remote procedure calls, powered by Protocol Buffer encoding. It is used in large distributed systems as well as on mobile devices, it supports bi-directional streaming and is built of HTTP/2 which allows for efficient and persistent connections. gRPC is implemented in a variety…


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OpenCensus for Java gRPC developers!

In this tutorial, we’ll examine how to use OpenCensus in your gRPC projects in the Java programming language for observability both into your server and then client! We’ll then examine how we can integrate with OpenCensus exporters from Jaeger and Google Stackdriver Tracing and Monitoring.

gRPC is a modern high performance framework for making remote procedure calls, powered by Protocol Buffer encoding. It is used in large distributed systems as well as on mobile devices, it supports bi-directional streaming and is built of HTTP/2 which allows for efficient and persistent connections. gRPC is implemented in a variety of languages like…


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OpenCensus Go for gRPC developers!

In this tutorial, we’ll examine how to use OpenCensus in your gRPC projects in the Go programming language for observability both into your server and then client! We’ll then examine how we can integrate with OpenCensus exporters from AWS X-Ray, Prometheus, Zipkin and Google Stackdriver Tracing and Monitoring.

gRPC is a modern high performance framework for remote procedure calls, powered by Protocol Buffer encoding. It is polyglot in nature, accessible and useable on a variety of environments ranging from mobile mobile devices, general purpose computers to data centres for distributed computing, and it is implemented in a variety of languages…


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One of the most used server caching and scaling technologies is Memcached http://memcached.org/ Memcached is a high performance, free and open source, distributed memory object caching system. It was created by Brad Fitzpatrick https://en.wikipedia.org/wiki/Brad_Fitzpatrick in 2003 as a solution to scale his social media product LiveJournal, by his company Danga Interactive https://memcached.org/

From the Alexa Top 500 list https://www.alexa.com/topsites, I can count for certain at least 11 of the top 20 sites that use Memcached as well as including some well known to developers to give: Amazon, Google, YouTube, Reddit, Facebook, Twitter, Github, Wikipedia, Airbnb, Adobe, Instagram, LiveJournal etc.

As…


In this post, we’ll examine how you can minimally add distributed tracing and monitoring to your web server written in Go, with OpenCensus https://opencensus.io This post has a couple of visuals and code snippets but ultimately the gist of it is a simple one that can easily be extended to more complex use cases, creating value and insights in your distributed systems.

One of the most important programs that many programmers begin with is a a program, to print “Hello, world!” to the screen, written in their programming language of choice. “Hello, world!” …


MongoDB driver instrumented with OpenCensus in Go

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The trio!

In this post, we’ll examine how I minimally and non-invasively instrumented the Go driver for MongoDB, to trace my entire app and glean useful insights into the behavior of my entire media search app.

Amongst NoSQL databases, one of the most popular is MongoDB. Throughout my journey in the software industry, I have always encountered the need for a database and my journey happens to occur in the era of NoSQL databases. I have used MongoDB for many years, mostly in the Go and Node.js programming languages and with MongoDB I have built numerous apps and products. Four days ago…


In this post, we’ll explore the power of OpenCensus’ exporters, using the Google Cloud Spanner package for both the Go and Java programming languages.

The Cloud Spanner package has already been instrumented using OpenCensus. Our mission is to add a few lines to already running code to harness this instrumentation, to extract metrics and traces. We’ll then export them to Stackdriver for recording, root cause analyses, visualization and other analyses — a typical task that Application Performance Management teams would perform.

The example is an excerpt of a microservice from a fictional athletics startup, ZeuSports. It is their database microservice(dBmus)…

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Observability and infrastructure for high performance systems and the cloud.

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