Run Kubernetes on MySQL, Postgres, sqlite, dqlite, not etcd.

High Performance Software-Defined Block Storage for container, cloud and virtualisation. Fully integrated with Docker, Kubernetes, Openstack, Proxmox etc.

RedisInsight is a visual tool that provides capabilities to design, develop and optimize your Redis application. Query, analyse and interact with your Redis data.

Scratch is an open-source alternative to BigQuery, Redshift, and Snowflake. Runs on Clickhouse.

A Terraform Provider for Namecheap domain DNS configuration.

Argo Workflows provides an excellent platform for infrastructure automation, and has replaced Jenkins as my go tool for running scheduled or event-driven automation tasks.

In growing my experience with Argo Workflows, I’ve killed clusters, broken workflows and generally made a mess of things. I’ve also built a lot of workflows that needed refactoring as they became difficult to maintain.

This blog post aims to share some of the lessons I’ve learned, and some of the patterns I’ve developed, to help you avoid the same mistakes I’ve made.

We've added the ability to lint Dockerfiles on demand in Depot. This post covers the top 10 most common Dockerfile linting issues we've seen flowing through Depot.

We often get questions like:

- How much data can I put in an Elasticsearch cluster?
- How many nodes can an Elasticsearch cluster have?
- What’s the biggest cluster that you’ve seen?

And while the 14-year-old in me is proud to say that we’ve done 24/7 support for clusters of 1000+ nodes holding many PB of data, I am quick to add that:

1. It doesn’t mean it’s a good idea to have clusters that big.
2. Such generic questions deserve more nuanced answers. Which is exactly what this blog post does. And it applies to OpenSearch as well as for Elasticsearch. And for the most part, to Solr (where the cluster state is stored in Zookeeper).

In this blog post, we aim to expand on the first 5 lessons shared by Google's Site Reliability Engineering team, offering a closer look at practical implementation examples.

This week, we're taking another significant step forward as we get into the critical stack of monitoring and alerting. Now, it's time to equip yourself with the knowledge and tools needed to keep an eye on systems, analyze performance, and respond quickly to any issues that may come up.

A log file highlighter

The microservices architecture adds more moving parts to the overall system, and this doesn’t come for free. The cost of fully embracing microservices is only worth paying if it can be amortized across dozens of development teams.

In distributed systems, failures and latency issues are inevitable. Services can fail due to overloaded servers, network issues, bugs, and various other factors. As engineers building distributed systems, we need strategies to make our services robust and resilient in the face of such failures. One useful technique is using retries.

This post discusses testing and validation for infrastructure-as-code (IaC) with HashiCorp Terraform. The insights and ideas presented here can surely be extended to IaC in general.

To meet the bandwidth requirements of new and future AI workloads—and stay committed to our sustainability goals—the Dropbox networking team recently designed and launched our first data center architecture using highly efficient, cutting edge 400 gigabit per second (400G) ethernet technology.

Gitness is an open source development platform packed with the power of code hosting and automated DevOps pipelines.