Operations | Monitoring | ITSM | DevOps | Cloud

Modern application development requires more work to ensure the development path and the data it produces are fully in sync, secure, optimized, and error-free. This responsibility has increasingly fallen upon application developers. They’re being asked to double as database administrators to maintain fluidity in the process and support an agency’s rapid release cycle.

To put it simply, serverless computing is a cloud computing execution model meaning that the cloud provider is dynamically managing the distribution of computer’s resources. What’s taking up valuable computing resources is the function execution. Both AWS and Azure charge more if you have a combination of allocated memory and the function execution elapse time which is rounded up to 100ms.

The Azure SQL Managed Instance is one of Microsoft’s Platform-as-a-Service (PaaS) offerings for SQL. It adds all the features you would expect of a PaaS platform such as automated patching, backups and streamlined high availability whilst closely aligning the technology to on-premises or IaaS workloads to reduce the barrier to entry. The product features near 100% compatibility with the latest Enterprise Edition of SQL Server and the automated Azure Data Migration service.

Query tuning is generally considered one of the fastest ways to accelerate your Microsoft SQL Server performance. System-level server performance improvement activities can be expensive and ineffective. Moreover, expert developers agree most SQL Server performance issues can be traced directly to poorly written queries and ineffective indexing rather than hardware constraints. In fact, many performance problems can only be resolved through query optimization and tuning.

This is the story of how I used Honeycomb to troubleshoot redis/redis-rb#924 and discovered a surprising workaround.

Apache Ignite is a computing platform for storing and processing large datasets in memory. Ignite can leverage hardware RAM as both a caching and storage layer to serve as a distributed, in-memory database or data grid. This allows Ignite to ingest and process complex datasets—such as those from real-time machine learning and analytics systems—in parallel and at faster speeds than traditional databases supported by only disk storage.

Hazelcast is a distributed, in-memory computing platform for processing large data sets with extremely low latency. Its in-memory data grid (IMDG) sits entirely in random access memory, which provides significantly faster access to data than disk-based databases. And with high availability and scalability, Hazelcast IMDG is ideal for use cases like fraud detection, payment processing, and IoT applications.

Most modern web applications are heavily reliant on persisting data with relational databases, and so it’s no surprise that a large part of application performance monitoring relates to keeping an eye on database performance to ensure that our SQL queries are as efficient as possible. With this in mind, Scout features a Database Addon module, and in this video we are going to take a closer look at what it has to offer.