Operations | Monitoring | ITSM | DevOps | Cloud

Over the years, containerization has grown in popularity among organizations and will continue to grow. For example, containerization is slowly becoming the de facto approach when it comes to building applications following the microservices architecture. It is undeniable that containerization has a lot of advantages, but these advantages come at a cost.

Over the past several years, I've helped numerous customers migrate SQL Server workloads to Azure SQL, including Azure SQL Database, Azure SQL Managed Instance, and Azure SQL Virtual Machines. In this article, I'll explain some of the challenges of optimizing the compute cost for an Azure SQL Database deployment and review how the serverless compute tier can greatly simplify it.

Enterprises are dealing with a deluge of observability data for both IT and security. Worldwide, data is increasing at a 23% CAGR, per IDC. In 5 years, organizations will be dealing with nearly three times the amount of data they have today. There is a fundamental tension between enterprise budgets, growing significantly less than 23% a year, and the staggering growth of data.

Recently, a critical out-of-bounds vulnerability, assigned to CVE-2021-44142, was disclosed in Samba versions prior to 4.13.17. The Samba vulnerability carries a critical CVSS of 9.9 and allows attackers to remotely execute code on machines running a Samba server with a vulnerable configuration. The vulnerability was disclosed as part of the Pwn2Own Austin competition where researchers are challenged to exploit widely-used software and devices with unknown vulnerabilities.

Just like many other production DevOps engineering teams, our JFrog team deploys new version releases several times a day to AWS, Azure and GCP, across more than 20 cloud regions. This process used to take us many hours and could have even failed if it was done alongside maintenance by other teams.

Today we are happy to announce that after month of work we finally can release Icinga for Windows v1.8.0. As discussed in our live Icinga for Windows Q&A on our YouTube-Channel, we spent lots of time resolving issues reported by our community and customers and in general improved the performance as well.

In our daily life we can face different difficulties. From spilling coffee on our clean shirt just before leaving home to not finding an emoji that satisfies us to answer that someone we like. Stupid little things compared to how difficult it is sometimes to identify network problems for an external IT provider.

In this article, we’ll deep dive into all the basics to help you decide if AWS RDS is the right decision for your architecture and help you hit the ground running if you do end up AWS RDS. For many decades now, relational databases (RDS) have been the place to store your data. They are pretty flexible often use some kind of SQL dialect, which is one of the main languages taught in computer science classes, and widely understood by the average developer.

Typically, Infrastructure-as-Code or IaCs have had their own languages to learn. For example, if leveraging Terraform most likely you came across Terraform’s native syntax, HCL. Though as software engineers we might be more familiar with other languages of choice. Using a general-purpose computer language vs a provider level syntax does unlock the power of the language; anything you can do in the computer language potentially can be additional methods, calls, etc.