Should you leave the cloud? Is cloud migration reversing? Is cloud repatriation a growing trend? On-premises vs. Cloud – which is best? How do you futureproof your IT and protect your business through recession or uncertainty, whether that’s in Cloud or On-prem? Today’s article is about keeping your options open within the context of recent economic and technological trends.
Behind the scenes, nearly every major web service has an API—an “Application Programming Interface”. APIs are bits of code that allow applications to pass data/information back and forth using a system of requests and responses. From booking your flight ticket to checking the weather forecast on your phone, APIs are everywhere.
What’s the ultimate goal of bringing observability into an organization? Is it just to chase down things when they’re broken and not working? Or can it be used to truly enable developers to innovate faster? That’s a topic I recently discussed with David Ostrovsky, a software engineer at Meta, the parent company of social media networks Facebook and Instagram among others. He was my guest on the most recent episode of the OpenObservability Talks podcast.
Devices, developers, applications, and services produce and utilize enormous amounts of JSON data every day. A portion of this data consists of time-stamped events or metrics that are a perfect match for storing and analyzing in InfluxDB. To help developers build the applications of the future, InfluxDB provides several ways to get JSON data into InfluxDB easily.
At Lumigo, we keep improving the coverage and quality of our distributed tracing instrumentation to give you, through Lumigo’s transactions, the most accurate and intuitive representation of how your distributed system behaves. In this blog, we cover a recent development for the Amazon SQS instrumentation in Lumigo’s OpenTelemetry distro for Python, providing a seamless experience for a scenario that otherwise would result in confusing, broken transactions and lost insights.
N+1 queries are the most common problems among developers. N+1 database query problems occur when you have to call the database for N items, and those N items have again N additional data fields which are not in the same table, and those extra N data fields are required for the use case. Generally, this issue is handled at the time of database designing, but every problem cannot be solved efficiently by one solution, some need to be solved by brute force.
Distributed architectures are becoming an increasingly important source of application services for organizations. Advances in observability and monitoring are being driven by this trend. But exactly how do observability and monitoring differ from one another? It's essential to know when something goes wrong in the application delivery chain so you can identify the root cause and resolve it before it has an impact on your business. Monitoring and observability offer a two-pronged strategy.
It’s hard to think of a use case that Grafana hasn’t been used for. When Torkel Ödegaard launched the Grafana open source project with his first commit in December 2013, “my goal was to make time series data accessible for a wider audience, to make it easier to build dashboards, and to make graphs and dashboards more interactive,” he said.
