Operations | Monitoring | ITSM | DevOps | Cloud

Log monitoring can be a tedious process. When you have logs, you generate numerous log files in the log database that you need to track. Though a log file parser can help you search through multiple or large logs easily, it’s typically one of those processes which we only look at once it stops working. The windows system logs contain operating system logs as well as logs from applications such as Internet Information Services (IIS) and SQL server.

Last October, I published a blog post describing the efforts we've committed to on the Bitbucket Cloud engineering team to achieve world-class reliability. A lot has happened in the past year (understatement of the year)! What the team has accomplished is tremendous, but we've also learned a thing or two that we can work further to improve.

Cloud is a driving force that is reshaping organizations to adapt their people and processes in embracing this game-changing technology. Recently, Mike Fonseca of HashiCorp published a Guide to Cloud Cost Optimization with HashiCorp Terraform, in which he details how Densify can seamlessly integrate with Terraform in to help ensure your enterprise infrastructure is always cost optimized.

Managing large numbers of checks by hand quickly becomes cumbersome. Luckily, Checkly's REST API allows us to automate most of the repetitive steps. Building on that API, the Checkly Terraform Provider takes automation one step further, enabling users to specify their active monitoring setup as code. In this article, we will be building on top of John Arundel's great intro from a few months back and showing how to manage multiple checks using groups and shared code snippets.

According to research from McKinsey, only 16% of digital transformation efforts have successfully improved performance and equipped the organizations to sustain changes in the long term. That’s a shockingly low number. Why is this happening? And how can you prevent this from derailing your own digital transformation journey and putting your business models, revenue, and profitability at risk?

HashiConf Digital October 2020 was the second HashiConf to be held online due to the coronavirus pandemic. It was held on October 14 and 15 on HashiCorp’s digital event platform. As of this writing, recordings of the talks are available on the platform, but they will be posted soon to HashiCorp’s YouTube channel.

Canonical, the publisher of Ubuntu, releases Charmed Kubeflow, a set of charm operators to deliver the 20+ applications that make up the latest version of Kubeflow, for easy consumption anywhere, from workstations to on-prem, public cloud, and edge. > Visit Charmed-kubeflow.io to learn more. Kubeflow provides the cloud-native interface between Kubernetes, the industry standard for software delivery and operations at scale, and data science tools: libraries, frameworks, pipelines, and notebooks.

Serverless architectures remove the need to provision and maintain infrastructure components like servers and containers, so developers can focus on writing and deploying code. However, serverless architectures also introduce new challenges to monitoring and observability. Teams building serverless applications can iterate quickly and deploy frequent code and configuration changes, making it difficult to track what impact these changes have on your applications.

Amazon Web Services (AWS) is a comprehensive cloud computing platform, providing an array of services to manage a business’s data infrastructure to help it grow and expand. With the wide range of services provided, it has multiple options to provide you with an elastic approach to optimize your costs. However, many users struggle with controlling their expenditure due to a variety of factors. Getting a complete understanding of how to reduce your AWS operational costs may be a daunting task.