If you are running a distributed system and have reached a point of scale where you’re running 5+ services, you are more than likely experiencing difficulties when troubleshooting. Does the following sound somewhat familiar?

Simple enough to be embedded in text as a sparkline, but able to speak volumes about your business, time series data is the basic input of Anodot’s automated anomaly detection system. This article begins our three-part series in which we take a closer look at the specific techniques Anodot uses to extract insights from your data.

It’s that time of year again–the temperature is dropping, snow is falling, and a new year has arrived. On the bright side, the end of 2018 brings the beginning of 2019 and a whole new list of tech conferences to look forward to.

The inherent limitations of most log managers and the need to work within the constraints of your current hardware may force your enterprise to make some hard choices. Less useful data may be left unchecked, old information will eventually get deleted, and the amount of data that is accessed in real-time is sacrificed to reduce excess workload.

If you rely on Elasticsearch for centralized logging, you cannot afford to experience performance issues. Slow queries, or worse — cluster downtime, is not an option. Your Elasticsearch cluster needs to be optimized to deliver fast results.

This bank needed to upgrade their customer recording communications analysis & troubleshooting abilities, to comply with required regulations. It was also important for them to identify and resolve problems proactively. By implementing XpoLog they managed to significantly shorten the ‘loss-of-recording’ durations, perform quick troubleshooting and get to the root cause fast. Their ability to analyze/monitor their environments became much simpler and more efficient.

The firm runs hundreds of services which optimize online advertising. The company utilizes large amounts of data which is located both on-premise and on AWS. They wanted to: By using XpoLog the company created a single location that manages all the information from all the sources. The information is shipped to the XpoLog cluster and tagged to the relevant service/team. XpoLog is deployed and managed on AWS spot instances, reducing approximately 90% of the required hardware costs! Try XpoLog free.