The latest News and Information on DevOps, CI/CD, Automation and related technologies.
In our previous blogs on Capturing Application State and using Ephemeral Containers for Debugging Kubernetes, we discussed the value of being able to deploy specific tools to gather diagnostics for later analysis, while also providing the responder to the incident the means to resolve infrastructure or application issues.
It is an old cliche adage, but there is no better statement than “a picture is worth a thousand words” that explains the effectiveness of visuals to deliver a message. Especially, in the data domain where a raw message often exists in numbers, visualizing graphs and charts is the best way to share information. When it comes to visualizing metrics from Graphite, there is no solution that can beat Grafana.
When it comes to identity and access management solutions, two names that often come up are Active Directory (AD) and Azure Active Directory (AAD). While many people are familiar with AD, AAD is still a relatively new concept to some. In this article, we will take a deep dive into both directories and explore their similarities, differences, pros, cons, and everything in between.
In the modern digital age, the migration of data and applications to the cloud has been a significant trend, prompted by the promise of increased efficiency, scalability, and reduced IT costs. Cloud services such as Microsoft’s Azure Cloud have become increasingly popular, offering a host of services including computing power, storage solutions, and advanced analytics.
Static application security testing (SAST) involves analyzing source code to identify and address potential security vulnerabilities. Using SAST early in development identifies threats before they can affect a live environment. SAST is particularly important for continuous integration and continuous deployment (CI/CD) pipelines. These pipelines automate the integration of new code changes into the main codebase and deploy applications to production environments.
Streaming Aggregation and Recording Rules are two ways to tame High Cardinality. What are they? Why do we need them? How are they different?
Navigating compliance requirements can be complex because there are so many of them, and there is a good chance that at least one set of standards applies to you. Standards can be for specific sectors, like The Health Insurance Portability and Accountability Act (HIPAA) for healthcare, or may apply more generally to organizations across industries, like the General Data Protection Regulation (GDPR).
.Organizations in every industry continue their transition to cloud services, and while this may be a step forward in general, it does bring with it its own unique set of challenges. Cloud use, and in particular CloudOps, relies on a complex and intricate infrastructure which is difficult to manage and maintain, and it's a critical part of keeping a business' networks functioning. This makes finding a way to simplify the use of CloudOps a top priority for many businesses, but does a solution exist?
This is the third and final post (for now) in the series about developing email templates with MJML and deploying them to AWS. In the previous post, we developed a Gulp script to automatically build HTML from the MJML file and insert it in a template file for AWS. In this post, we will set up an automated build and deployment of the email template using Azure DevOps. A quick recap.
