Operations | Monitoring | ITSM | DevOps | Cloud

We’ve got some outstanding news to share in the arena of security partnerships: Logz.io® Cloud-based SIEM has officially achieved Amazon Web Services (AWS) Security Competency! This designation within the Logging, Monitoring, SIEM, Threat Detection, and Analytics category further demonstrates Logz.io’s proven commitment to delivering best-in-class security.

Rightsizing is about finding the optimal cloud configuration options to ensure that you get the performance you need—within any given constraints you are operating under—at the lowest possible cost. This is a simple proposition, but deceptively so. For one thing, business requirements are constantly changing, meaning that your workloads must adapt to support them, which in turn changes their operating parameters.

In my previous blog posts, I talked about some of the most essential best practices you should have while working with the Azure Logic App: And some tips and tricks: Today I’m going to speak about another critical Best practice, Tips, and Tricks: implementing Error handling inside Logic Apps.

As we push more data to the cloud, avoidable mistakes are hampering migration. The biggest culprit: messy data with inadequate security and integration.Data transfers seem to be the easiest part of cloud migration. After all, migrating applications is the biggest pain in the neck. Data replication and migration should be simple, something that’s done during the last step of the application and data migration process. Right?

As a framework for goal-setting, the Objectives and Key Results (OKRs) methodology is an incredibly useful tool when implemented properly. It can help your engineering team better plan and stay aligned toward common objectives through the duration of the development process. On an individual level, OKRs can also encourage each team member to make personal progress toward their own goals or common team goals that would benefit the company.

When designing a solution, you should keep future needs in mind. If the number of users increases dramatically in a short period of time, the solution should be scalable enough to handle the new growth. Making systems scalable on cloud is relatively easier as compared to scaling on-premises infrastructure. AWS has provided excellent tools/services to enable your applications for as much scalability as you want.

If you have worked in any part of the application delivery lifecycle long enough, there’s a very good chance you have directly used or been a consumer of Nagios. For a period of time in the early 2000s, it was the go-to solution for basic server monitoring and alerts. Fast forward 20 years and you might be surprised how many organizations still rely on Nagios for mission critical workloads — although not without a fair amount of duct tape and super glue challenges.

AWS currently offers over 200 services. Some of those make up the AWS Cost Management suite. This group comprises AWS Cost and Usage Report (CUR), AWS Budgets, AWS Cost Explorer, AWS Cost Categories, and AWS Cost Anomaly Detection. Budgets and Cost Explorer are an excellent pair of complementary tools in this group. They have similarities that cause users to wonder if they need both and, if so, why. Here is a brief overview of the differences between AWS Budgets and Cost Explorer.