In the first article, we talked about CI or Continuous Integration. This post looks at the second half of the CI/CD acronym, Continuous Delivery. Continuous delivery takes the build originating in the CI process and puts it into an acceptance environment for further evaluation before promoting the code to production (the released version). To back up a moment, CI is the planning, coding, testing, and building of software in a rapidly repeating process.
No matter which path of the stack you work on, it’s crucial you make sure your website or API is up and running. We wanted to create a tool that can give you superpowers. Enter, Sematext Synthetics! You can monitor the availability of APIs and websites as well as their performance, and user journeys. This means 24×7 monitoring from multiple locations around the globe with alerts when things go wrong!
Whilst researching recent client-side attacks our security team observed a highly-sophisticated self-cleaning and self-destructing skimmer on the popular hardware tool website Greenworks. The hack was first spotted by RapidSpike’s Client-Side Security Scanner on June 8th, and at the time of writing, the hack is still live on www.greenworkstools.com/.
The just-released Prometheus v2.19.0 introduces the new feature of memory-mapping full chunks of the head (in-memory) block from disk, which reduces memory usage and also makes restarts faster. I will be talking about this feature in this blog post.
Proactive database performance monitoring is essential to maintain resource utilization and system performance. As data volumes grow, it is critical to monitor databases properly to deliver a seamless enduser experience, and lower IT infrastructure costs. Pinpointing database issues as they occur can assist in faster troubleshooting, and keeping the health of the application intact. Without monitoring, database outages may go unnoticed, and lead to loss of business reputation and profit.
To understand what’s going on in their environment, DevOps teams usually ship some combination of logs, metrics and traces—depending on which signals they’re hoping to monitor. Each data type will expose different information about what is happening in a system. However, not all of that information will be helpful on a day-to-day basis, which can rack up unnecessary data storage costs. That should require users start to filter telemetry data across their observability stacks.
