Azure Knowledge Explorer (ADX), a part of Azure Synapse Analytics, is a extremely scalable analytics service optimized for structured, semi-structured, and unstructured knowledge. It offers customers with an interactive question expertise that unlocks insights from the ocean of ever-growing log and telemetry knowledge. It’s the excellent service to investigate excessive volumes of recent and historic knowledge within the cloud through the use of SQL or the Kusto Question Language (KQL), a strong and user-friendly question language.
Azure Knowledge Explorer is a key enabler for Microsoft’s personal digital transformation. Just about all Microsoft services and products use ADX in a technique or one other; this consists of troubleshooting, analysis, monitoring, machine studying, and as an information platform for Azure companies corresponding to Azure Monitor, PlayFab, Sentinel, Microsoft 365 Defender, and lots of others. Microsoft’s clients and companions are utilizing ADX for a big number of situations from fleet administration, manufacturing, safety analytics options, bundle monitoring and logistics, IoT gadget monitoring, monetary transaction monitoring, and lots of different situations. Over the past years, the service has seen phenomenal progress and is now operating on tens of millions of Azure digital machine cores.
Final yr, the third technology of the Kusto engine (EngineV3) was launched and is at present supplied as a clear, in-place improve to all customers not already utilizing the most recent model. The brand new engine contains a utterly new implementation of the storage, cache, and question execution layers. Consequently, efficiency has doubled or extra in lots of mission-critical workloads.
Superior efficiency and cost-efficiency with Azure Knowledge Explorer
To higher assist our customers assess the efficiency of the brand new engine and value benefits of ADX, we seemed for an present telemetry and logs benchmark that has the workload traits widespread to what we see with our customers:
- Telemetry tables that comprise structured, semi-structured, and unstructured knowledge varieties.
- Information within the a whole lot of billions to check large scale.
- Queries that symbolize widespread diagnostic and monitoring situations.
As we didn’t discover an present benchmark to satisfy these wants, we collaborated with and sponsored GigaOm to create and run one. The brand new logs and telemetry benchmark is publicly accessible on this GitHub repo. This repository features a knowledge generator to generate datasets of 1GB, 1TB, and 100TB, in addition to a set of 19 queries and a take a look at driver to execute the benchmark.
The outcomes, now accessible within the GigaOm report, present that Azure Knowledge Explorer offers superior efficiency at a considerably decrease value in each single and high-concurrency situations. For instance, the next chart taken from the report shows the outcomes of executing the benchmark whereas simulating 50 concurrent customers:
Study extra
For additional insights, we extremely advocate studying the total report. And don’t simply take our phrase for it. Use the Azure Knowledge Explorer free providing to load your knowledge and analyze it at excessive velocity and unmatched productiveness.
Take a look at our documentation to search out out extra about Azure Knowledge Explorer and be taught extra about Azure Synapse Analytics. For deeper technical info, try the brand new guide Scalable Knowledge Analytics with Azure Knowledge Explorer by Jason Myerscough.
