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The success of IT monitoring relies in part on the accuracy and variety of IT logs that applications generate. But as IT environments grow more complex and distributed, the number and size of log files multiplies exponentially, which makes it difficult to manage logs manually.
Below are six recent SearchITOperations articles that explore ways to optimize an IT log management strategy in light of these modern challenges.
Machine learning deepens insight
IT logging tools with machine learning capabilities offer all or most of the same features as standard logging tools -- such as visualization, time-series data analysis and the ability to parse any type of log -- but they also add more specialized features, such as anomaly flagging, regression analysis and correlation, and the ability to make predictions. IT expert Walker Rowe digs into the extended visibility that machine learning can bring to log analysis.
Prepare for the challenges of AI-based logging
This article from IT architect Brian Kirsch further examines why IT organizations should consider AI as part of a log management strategy. AI enables a log analytics tool to parse extensive files from multiple sources efficiently, as well as unearth the root causes of an issue. However, AI isn't a cheap endeavor, and there are many ways for organizations to incur extra, unexpected expenses.
Containers bring new logging demands
Containers' ephemeral lifespans and unique security requirements increase logging complexity in a number of ways. Senior technology editor Stephen Bigelow identifies four common approaches to IT log management for large-scale container deployments.
Weigh big data logs versus big data costs
IT log management has transcended its optional role in the IT application environment to one of utter necessity -- especially as those environments advance in complexity and generate more and more logs. But as log output expands into another form of big data, some IT organizations find that their log storage and management services soar to the top lines of their budgets. Senior news writer Beth Pariseau explores certain IT log management best practices, and updated tools and features, that create more cost-effective options.
Log analytics eases monitoring overload
Microservices complicate an IT log management strategy as much as containers do, with significantly increased production volume. For Tel Aviv, Israel-located biometrics firm BioCatch, for example, a move to microservices caused its log volume to triple. And not only did the volume become unmanageable, but so did analysis. Pariseau examines BioCatch's choice of Coralogix for log management, as well as broader changes in the IT logging and monitoring market to address feature gaps related to microservices.
Grafana offers Loki for better Kubernetes monitoring
Grafana Loki isn't an exact replacement for IT logging tools such as Elasticsearch, but it does offer efficient log storage and processing at a low cost. Paytm Insider, based in Mumbai, saved a whopping 75% on log storage costs, for example, ingesting millions of logs per hour across applications and services. Read about Grafana Loki's features that enable these savings with this article from Pariseau.