If you’re familiar with Telegraf, you know that you can easily configure this lightweight collection agent with a single TOML configuration file to gather metrics from over 180 inputs and write data to a wide variety of different outputs and/or platforms. You might also know that Telegraf can act as a processor, aggregator, parser, and serializer.
An abundance of information can be daunting for any company. If internal teams do not know where the data is, it might hamper their efficiency at the cost of data quality and cleanliness. From a cost-effectiveness viewpoint, organizations are likely to waste excessively by hanging on to redundant data or storing varied data in one location irrespective of their sensitivity level.
5G is in the process of transforming communications technology, enabling never-before-seen data transfer speeds and high-performance remote computing capabilities.
The telecom industry is in the midst of a massive shift to new service offerings enabled by 5G and edge computing technologies. With this digital transformation, networks and network services are becoming increasingly complex: RAN, Core and Transport are only a few of the network’s many layers and integrated components. Today’s telecom engineers are expected to handle, manage, optimize, monitor and troubleshoot multi-technology and multi-vendor networks.
Data platforms — or databases with sets of APIs for flexibly working with data — are quintessential backbones for those who rely heavily on being able to change how they obtain data and work with their data over time. A good data platform will provide you the necessary tools to glean the insights you need to solve tangible problems. That platform should also hopefully make it so you don’t have a bad time doing it!
Today, I’m happy to share more about our partnership and commitment to our users that they will have the best possible experience of both Elasticsearch and Grafana, across the full breadth of Elasticsearch functionality, with dedicated engineering from both Grafana Labs and Elastic. Through joint development of the official Grafana Elasticsearch plugin users can combine the benefits of Grafana’s visualization platform with the full capabilities of Elasticsearch.
Splunk is a fantastic platform for ingesting, storing, searching and analysing data from logs, metrics and traces from a massive variety of sources. But does that mean we should ignore all of that data that doesn’t fall into these categories, like image and video data for example? Of course not!
Cache is king for speedy data retrieval. So if you’re interested in how Elasticsearch leverages various caches to ensure you are retrieving data as fast as possible, buckle up for the next 15 minutes and read through this post. This blog will shed some light on various caching features of Elasticsearch that help you to retrieve data faster after initial data accesses.
