Overview

Sumo Logic

Stacks192

Followers282

Votes21

Serilog

Stacks2.1K

Followers107

Votes1

GitHub Stars7.8K

Forks840

Serilog vs Sumo Logic: What are the differences?

Deployment: Serilog is a .NET logging library that writes structured log events to sinks, while Sumo Logic is a cloud-based log management and analytics service. This key difference lies in the deployment approach - Serilog is a library that needs to be integrated into the .NET application, whereas Sumo Logic is a SaaS solution accessed through the cloud.
Integration: Serilog is designed to integrate seamlessly with the .NET ecosystem, utilizing sinks to output log events to various destinations. On the other hand, Sumo Logic offers integrations with a wide range of technologies and services beyond the .NET framework, making it versatile for a diverse set of environments.
Functionality: Serilog primarily focuses on providing a structured logging experience within .NET applications, enabling developers to log events in a meaningful way. In contrast, Sumo Logic offers comprehensive log management features such as log parsing, aggregation, and visualization, along with advanced analytics capabilities for monitoring and troubleshooting.
Pricing Model: Serilog, being a logging library, is generally free to use within applications once integrated. Sumo Logic, being a cloud service, operates on a subscription-based pricing model that typically involves costs based on data volume and features used, making it a paid service.
Scalability: Serilog's scalability is tied to the infrastructure and resources of the application where it is integrated, possibly requiring additional configurations for high-scale environments. Sumo Logic, being a cloud-based service, inherently provides scalability by leveraging its infrastructure to handle varying log volumes and processing demands efficiently.
Management and Maintenance: With Serilog, developers are responsible for managing and maintaining logging configurations within the application codebase, including updates and troubleshooting. Sumo Logic, as a managed service, handles the backend infrastructure, maintenance, and updates, relieving users of such operational tasks.

In Summary, Serilog and Sumo Logic differ in deployment, integration, functionality, pricing model, scalability, and management approaches when it comes to logging and log management solutions.

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Detailed Comparison

Sumo Logic	Serilog
Cloud-based machine data analytics platform that enables companies to proactively identify availability and performance issues in their infrastructure, improve their security posture and enhance application rollouts. Companies using Sumo Logic reduce their mean-time-to-resolution by 50% and can save hundreds of thousands of dollars, annually. Customers include Netflix, Medallia, Orange, and GoGo Inflight.	It provides diagnostic logging to files, the console, and elsewhere. It is easy to set up, has a clean API, and is portable between recent .NET platforms.
Ability to collect data from on-premise sources, private/public/hybrid clouds, and SaaS/PaaS environments;Real-time continuous query engine that constantly updates dashboards and reports for immediate visualization;Anomaly detection engine that enables companies to proactively uncover events without writing rules;LogReduce, our pattern-recognition engine, that distills tens/hundreds of thousands of log messages into a set of patterns for easier issue identification and resolution;The ability to support data bursts on-demand with our elastic log processing architecture;Real-time alerts and notifications	Structured logging; .NET logger
Statistics
GitHub Stars -	GitHub Stars 7.8K
GitHub Forks -	GitHub Forks 840
Stacks 192	Stacks 2.1K
Followers 282	Followers 107
Votes 21	Votes 1
Pros & Cons
Pros 11 Search capabilities 5 Live event streaming 3 Pci 3.0 compliant 2 Easy to setup Cons 2 Expensive 1 Missing Monitoring 1 Occasionally unreliable log ingestion	Pros 1 It's a logging library Cons 1 You can't compare this to seq 1 They are two different things
Integrations
Amazon CloudFront Amazon S3 Akamai AWS CloudTrail	.NET C++ LogRocket ASP.NET

What are some alternatives to Sumo Logic, Serilog?

Papertrail

Papertrail helps detect, resolve, and avoid infrastructure problems using log messages. Papertrail's practicality comes from our own experience as sysadmins, developers, and entrepreneurs.

Logmatic

Get a clear overview of what is happening across your distributed environments, and spot the needle in the haystack in no time. Build dynamic analyses and identify improvements for your software, your user experience and your business.

Loggly

It is a SaaS solution to manage your log data. There is nothing to install and updates are automatically applied to your Loggly subdomain.

Logentries

Logentries makes machine-generated log data easily accessible to IT operations, development, and business analysis teams of all sizes. With the broadest platform support and an open API, Logentries brings the value of log-level data to any system, to any team member, and to a community of more than 25,000 worldwide users.

Logstash

Logstash is a tool for managing events and logs. You can use it to collect logs, parse them, and store them for later use (like, for searching). If you store them in Elasticsearch, you can view and analyze them with Kibana.

Graylog

Centralize and aggregate all your log files for 100% visibility. Use our powerful query language to search through terabytes of log data to discover and analyze important information.

Sematext

Sematext pulls together performance monitoring, logs, user experience and synthetic monitoring that tools organizations need to troubleshoot performance issues faster.

Fluentd

Fluentd collects events from various data sources and writes them to files, RDBMS, NoSQL, IaaS, SaaS, Hadoop and so on. Fluentd helps you unify your logging infrastructure.

ELK

It is the acronym for three open source projects: Elasticsearch, Logstash, and Kibana. Elasticsearch is a search and analytics engine. Logstash is a server‑side data processing pipeline that ingests data from multiple sources simultaneously, transforms it, and then sends it to a "stash" like Elasticsearch. Kibana lets users visualize data with charts and graphs in Elasticsearch.