Operations | Monitoring | ITSM | DevOps | Cloud

The latest News and Information on Log Management, Log Analytics and related technologies.

Entity empowered troubleshooting

Modern applications are sufficiently instrumented and complex, creating a swell of data that's hard to navigate, parse and understand without proper context. Entities provide the backbone of your data streams, enabling you to tie all the individual measurements back to the objects and their interactions that happen on your actual stack. By traversing entities and overlaying raw data, Sumo Logic can help tie together raw signals with root causes.

Case study: Genesys' journey to the cloud and DevOps excellence

Continuous improvement and learning are two of the core tenets of the Genesys Cloud Native solutions team. In this session, Kal Patel, Principal Architect at Genesys will discuss how they use Sumo Logic Analytics across the company (from engineering, ops to security to customer support). Kal will also share insights on how the continuous improvement and learnings mindset has influenced his organization.

Ronald van Loon & Sendur Sellakumar | Splunk Cloud Is Rebuilt for the Data Age

Data analyst Ronald van Loon sits down with Splunk’s Sendur Sellakumar to discuss how companies can succeed in the data age. The conversation covers shifting to a cloud-native experience, honing in on a data-to-everything strategy, and customer-centric approach to data and product development. The majority of organizations are not prepared for an influx of data on the scale promised by the dawning data age. To thrive, every organization needs a complete view of its data — real-time insights with the ability to take real-time action.

What You Need to Know About IoT Logging

The Internet of Things (or, IoT) is an umbrella term for multiple connected devices sharing real-time data, and IoT logging is an important part of this. Troubleshooting bug fixes, connection problems, and general malfunctions rely heavily on logs, making them an invaluable asset not only in designing systems but also in system maintenance. To maximize system potential, this plethora of generated data needs to be managed efficiently.

Announcing auto-complete with type hints in the Elasticsearch Python client

Python introduced support for type hints in Python 3.5 via PEP 484, allowing tools like Mypy and Pyright to check your Python code for type conflicts before execution. This also helps tools that provide code auto-complete — like IDE, IPython, and Jupyter Notebooks — by providing a complete function signature, even for functions that are generated on import time like the Elasticsearch Python client.