September 2018 Summaries

Processing time series data is a crucial aspect of extracting insights from large amounts of sequential data, and various options are available for this purpose, including streaming frameworks such as Apache Kafka and Apache Spark Streaming, which allow for real-time processing of data streams. Google's recent announcement of its Cloud Inference API is seen as an exciting development in the field, offering a scalable and efficient way to process time series data, with companies like InfluxData expressing enthusiasm for its adoption and evolution. The article highlights the importance of proper data processing techniques, such as those offered by streaming frameworks, to uncover meaningful insights from time series data.

The deployment of serverless platforms is a topic of increasing interest as these platforms become more popular, with advantages including improved agility and cost savings. While acknowledging the benefits, the author also notes that there are hurdles ahead for serverless to become mainstream. Serverless is not necessarily tied to or exclusive to Kubernetes or microservices platforms, but can be used in conjunction with them, as noted by David Simmons, IoT Developer Evangelist at InfluxData. According to Simmons, serverless is well-suited for deploying small and specific functions within an application, whereas Kubernetes is better suited for larger, more complex applications.

This article from Database Trends and Applications highlights the growing importance of data-centric companies effectively managing their data for better decision-making. Industry experts point to rising trends such as Artificial Intelligence (AI) and Machine Learning (ML), which are increasingly being used to inform business decisions in various sectors including manufacturing, automotive, healthcare, and IT. The interview with InfluxData's VP of Products Tim Hall emphasizes the shift towards machine learning and autonomy in multiple industries, suggesting a significant transformation in how data is managed.

Telegraf is now integrated with Microsoft's Azure Monitor solution, expanding the types of metrics that can be collected and stored in the platform. The integration allows users to collect performance and utilization metrics from Azure resources and plot them in the Azure portal. Telegraf's open source nature and ease of use have contributed to its strength, as evident in its latest release with new plugins and community contributions. Deploying Telegraf on a Linux VM in Azure is straightforward, and a detailed set of instructions is available for users who want to learn more or try the solution themselves.

InfluxData's Telegraf to Integrate with Microsoft Azure Monitor to Expand Metrics and Event Collection Capabilities` InfluxData, a modern Open Source Platform for metrics, events, and time series data, has announced that its Telegraf Agent will integrate with Microsoft Azure Monitor. This integration enables Azure users to leverage the growing open source community contribution of Telegraf and expand their metrics and event collection capabilities. With this integration, Azure Monitor can now provide visibility into system health and application performance in Azure, while also supporting custom metrics using Telegraf plugins. The inclusion of Telegraf will enable Azure customers to use InfluxData as the time series database backend, making it easy to migrate all metrics to a single store. This collaboration validates InfluxData's decision to base its products on open source, highlighting the commitment and contributions from the Telegraf community.

Database indexes are used to improve the performance of database queries by creating a data structure that facilitates faster lookup, insertion, and deletion operations. The main purpose of a database index is to enable efficient retrieval of specific data from a large database. Database indexes can be created on any field in a table, but not all fields should be indexed equally, as some may have varying levels of selectivity, or the frequency with which they are used in queries. The type of database also plays a role in indexing, with relational databases often using B-tree indexes and NoSQL databases sometimes using hash indexes. InfluxDB's unique approach to indexing, where data inserted as a tag is indexed while data inserted as a field is not, can provide significant performance advantages.

The developers at InfluxDB and Telegraf have released new versions, 1.8.0 for Telegraf and 1.6.3 for InfluxDB, with a focus on adding new features and improving performance. The Telegraf release includes the addition of plugins for Azure Monitor, VMware vSphere, Kafka, Splunk, ActiveMQ, Beanstalkd, File Count, Icinga2, Kibana, PgBouncer, Temperature, Tengine, VMware vSphere, X509 Cert, Enum, Parser, Rename, and Strings. Additionally, new processors have been added, including ValueCounter, which counts the occurrence of values in fields. The release also includes improvements to outputs, parsers, and serializers for better data processing and consumption. InfluxDB 1.6.3 brings maintenance updates, including fixes for inherited intervals, derivatives, and other functions, as well as improved query compilation.

To enable machine learning systems to realize real-time decision making benefits, organizations need a time series database that can collect and analyze streaming data in real-time. InfluxData's unique platform uniquely handles massive volumes of streaming data generated at rapid rates from IoT sensors and gauges, then compresses the data so it doesn't consume storage capacity. With InfluxData, developers can train machine learning algorithms leveraging streaming data inputs to make decisions and take action in real-time, enabling self-learning and self-healing of systems. The platform provides a comprehensive set of tools and services to accumulate metrics and events data, analyze the data, and act on the data via powerful visualizations and notifications, supporting DevOps initiatives, IoT applications, and real-time analytics applications. InfluxData has rapidly built its developer and customer base across industries, with over 420 customers including Cisco Systems, Coupa Software, IBM, Houghton Mifflin Harcourt, Nordstrom, and Tesla, who have selected InfluxData as their modern data platform for metrics and events.

InfluxData's Time Series Database, InfluxDB, has been announced to enable the real-time decision making and self-healing capabilities of machine learning systems by providing high-quality, real-time data. Machine learning solutions are only as good as the data they collect, and InfluxDB delivers this critical component. The platform also supports time series data, a fundamental type for machine learning algorithms. Several customer use cases demonstrate how InfluxData's Time Series Platform can deliver the benefits of machine learning.

This article by Database Trends and Applications highlights the "Big Data 50" list of forward-thinking companies driving innovation in the big data market. The list aims to identify new and disruptive technologies in this rapidly changing field, with InfluxData featured as one of the companies. InfluxData is recognized for its Time Series Platform, which empowers developers to build next-generation monitoring, analytics, and IoT applications that deliver real business value quickly.

HashiCorp has partnered with InfluxData to provide tools for managing infrastructure, leveraging open-source technologies. The partnership allows users to manage both physical and virtual machines, as well as SaaS and IaaS environments. A Terraform module is now available for InfluxDB, enabling easy deployment and scaling of the database on AWS. This collaboration aims to improve the overall working infrastructure for applications, making it easier to scale monitoring and analytics platforms.

Thanks Minneapolis - See You Again! By Chris Churilo / Use Cases, Developer Sep 11, 2018 Navigate to: We just finished up our inaugural InfluxData Roadshow event in Minneapolis today, and we really enjoyed meeting everyone who joined us. Mark Herring, CMO at InfluxData, kicked off the morning with a review of the company’s vision and shared some insights into some of our latest customer case studies. They range from a secure email provider gaining GDPR compliance with InfluxDB & Kapacitor, to a biomass plant with an Industrial IoT use case, and finally, a review of retail giant, Wayfair, giving their Real User Monitoring (RUM) a major upgrade and migrating from their legacy Graphite backend to InfluxDB. Founder and CTO, Paul Dix, then followed with an in-depth review of the roadmap followed by an update to Flux, the new query language that he and the team have been working on. The second half was led by Anais Dotis-Georgiou, one of our Developer Advocates, who provided a training on InfluxDB and Architecting InfluxDB Enterprise. We built these sessions with a focus on educating and enabling our users to instrument and automate any system, application and business process across a variety of use cases. The team is still on the road, and there’s plenty of time to register for the next three hot spots of Austin, Seattle, and Denver. And let us know if you want us to come to your city! Here is the link to register and get more details. Get ready Austin, here we come!

InfluxData has partnered with PagerDuty through their Integration Partner Program, enabling customers to automate the resolution of issues related to metrics and events, allowing for faster and more efficient operations. This integration utilizes Kapacitor's processing framework to create alert rules that can be triggered when specific conditions are met, sending alerts directly to PagerDuty staff. The integration is well-suited for use cases such as DevOps and IoT monitoring, where real-time data analysis and automation of issue resolution can provide significant benefits. By leveraging this partnership, customers can improve their operations and innovate more efficiently.

InfluxDays SF 2018 is an upcoming event that promises to be exciting for InfluxDB users, with a great lineup of speakers from the InfluxData team and other experts sharing their knowledge and experiences on various topics related to time series data and the TICK Stack. The event will feature multiple tracks for workshops, allowing attendees to learn and network with developers and industry experts. Special early registration prices are available until September 14, 2018, making it an attractive opportunity for those interested in learning more about InfluxDB and its applications.

In a recent article, InfluxData IoT Developer Evangelist David Simmons discusses why the debate between serverless and Kubernetes isn't a real one when it comes to choosing the best fit for deployment. He explains that both architectures have their own strengths and weaknesses, with Kubernetes designed for container-based applications but facing ongoing pain points in adoption, while serverless alternatives offer advantages such as scalability and cost-effectiveness. Simmons notes that successfully deploying either architecture depends on knowing when and how to decide which one is best suited for a particular use case, acknowledging that the transition from one architecture to another may not always be a definitive end point, but rather a stepping stone towards new solutions.

OpenCensus is a collection of libraries designed to increase the observability of systems by providing APIs for gathering metrics and trace data, adding tags, and sending that data to a backend for storage. It provides standards-based instrumentation, including exporters for metrics and traces, such as the Prometheus exporter, which uses the Prometheus exposition format. OpenCensus is integrated with Telegraf, an InfluxData collection agent, allowing for seamless interaction and easy collection of data from OpenCensus-instrumented applications. The project enables developers to collect metrics by editing a few lines in the Telegraf configuration file and enabling the Prometheus plugin, making it easy to expose metrics in the Prometheus exposition format.

Chronograf 1.6.2 has been released, bringing enhancements to the Log Viewer page, including the ability to quickly copy log messages and support for negative filtering when searching using the minus sign. The release also includes a fix for leaking sockets on the Alert Rules page and re-adds notification functionality in dashboards. Binaries for the open source release are available on the downloads page.

InfluxData has been selected to present at several industry events worldwide to address growing interest in time series platform knowledge and expertise, as metrics, events, and other time-based data are being generated at an exponential rate. The company's InfluxDB database is the leading Time Series Database management system, according to DB-Engines' latest results. InfluxData will participate in events such as JAZOON Tech Days, DevOps Raleigh, DevOps Boston, Golab Florence, and Embedded Linux Conference + OpenIoT Summit Europe, where experts like Gianluca Arbezzano and Katy Farmer will present on topics like distributed monitoring, database metrics, and IoT data analysis. The company's unique features enable customers to build monitoring, alerting, and notification applications, as well as real-time analytics applications supporting streaming data and anomaly detection. With over 420 customers, including major brands like Cisco Systems, Coupa Software, and Tesla, InfluxData is pioneering the shift to time series in a modern metrics and events platform, empowering developers to build next-generation monitoring, analytics, and IoT applications faster, easier, and to scale.