1. Users Manage Terabytes of Data with Powerful and Agnostic Hosting from Azure Cloud Service
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“Given the challenges we face both in dealing with important volumes and high growth, it was obvious we needed to benefit from the cloud. Thanks to Azure, we were able to scale from gigabytes to terabytes of ingested data every day.” – Emmanuel Gueidan, CTO, Logmatic.io
SITUATION
Logmatic.io collects its clients’ machine data, all logs, metrics and events, enriches them, then displays them via the Logmatic.io web app. Clients navigate their platform, filtering and querying through those large amounts of data. Logmatic’s systems run around the clock and fuel critical decisions for clients, so it needed to build a system that could handle large amounts of data and could scale, while offering outstanding stability.
MICROSOFT AZURE ISV:
Logmatic.io
WEB SITE:
LOCATION: Paris, France
ORG SIZE: 16 employees
MICROSOFT AZURE ISV PROFILE:
Logmatic.io is an Operations Data Platform for Log and Machine events. It helps companies improve their software and business performance by leveraging their machine data. Companies get a clear overview of what is happening across distributed environments and spot the needle in the haystack in no time.
SOLUTION
Using a mix of D- and recently released F-series Microsoft Azure Virtual Machines gives Logmatic perfect flexibility in balancing RAM and CPU usage. It is key for Logmatic to efficiently manage the amount of data it deals with each day and ensures the most efficient system for clients. Spinning up new servers is quick, and arranging them neatly in resource groups gives it the right tools to build a scalable and manageable infrastructure. Thanks to Azure Load Balancer, Logmatic can expand its infrastructure transparently.
BENEFITS
Logmatic utilizes the flexibility of Azure to create an agnostic hosting environment that deals easily with Microsoft and non-Microsoft technologies.
Azure scalability enables virtual machines to help Logmaitc achieve real-time performance in answering client requests with massive amounts of data.