SkySQL uses best-of-breed software, and when it comes to metrics and monitoring that means Prometheus and Grafana. SkySQL Monitor is built on both, and provides customers with interactive dashboards for both real-time and historic metrics monitoring. In addition, it meets the same high availability and security requirements as other SkySQL components, ensuring metrics are always available and always secure.
In this session, we’ll explain how SkySQL Monitor works, walk through its dashboards and show how to monitor key metrics for performance and replication.
SkySQL is the first and only database-as-a-service (DBaaS) to perform workload analysis with advanced deep learning models, identifying and classifying discrete workload patterns so DBAs can better understand database workloads, identify anomalies and predict changes.
In this session, we’ll explain the concepts behind workload analysis and show how it can be used in the real world (and with sample real-world data) to improve database performance and efficiency by identifying key metrics and changes to cyclical patterns.
Faster, better, stronger: The new InnoDBMariaDB plc
For MariaDB Enterprise Server 10.5, the default transactional storage engine, InnoDB, has been significantly rewritten to improve the performance of writes and backups. Next, we removed a number of parameters to reduce unnecessary complexity, not only in terms of configuration but of the code itself. And finally, we improved crash recovery thanks to better consistency checks and we reduced memory consumption and file I/O thanks to an all new log record format.
In this session, we’ll walk through all of the improvements to InnoDB, and dive deep into the implementation to explain how these improvements help everything from configuration and performance to reliability and recovery.
This document summarizes a company's migration from their old MySQL database to MariaDB Columnstore to address scalability issues. They identified alternative databases, chose MariaDB Columnstore for its performance and support. They saw a 71% reduction in query times after migrating and refactored their ETL processes and application to take advantage of the new database. While deployment had some challenges around storage capacity, they were able to automate cluster creation and define a migration process to successfully move to the new database.
What to expect from MariaDB Platform X5, part 2MariaDB plc
This document summarizes new features and enhancements in MariaDB MaxScale 2.5 and MariaDB ColumnStore 1.5. Some key points include:
- MaxScale 2.5 includes a new graphical user interface, improved binlog router, capability to stream binlogs to Kafka as JSON, and distributed caching between MaxScale servers.
- ColumnStore 1.5 features a new API, PowerBI direct query connector, improved replication from InnoDB, and multinode support in SkySQL.
- Configuration and installation of ColumnStore has been simplified, including using a new ColumnStore.xml utility and S3 storage manager for redundant file storage in object storage.
How QBerg scaled to store data longer, query it fasterMariaDB plc
The continuous increase in terms of services and countries to which QBerg delivers its services requires an ever-increasing load of resources. During the last year QBerg has reached a critical point, storing so much transactional data that standard relational databases were unable to meet the SLAs, or support the features, required by customers. As an example, they had to cap web analytics to running on a maximum of four months of history. The introduction of MariaDB ColumnStore, flanked by existing MariaDB Server databases, not only will allow them to store multiple years’ worth of historical data for analytics – it decreased overall processing time by one order of magnitude right off the bat. The move to a unified platform was incremental, using MariaDB MaxScale as both a router and a replicator. QBerg is now able to replicate full InnoDB schemas to MariaDB ColumnStore and incrementally update big tables without impacting the performance of ongoing transactions.
ClustrixDB: how distributed databases scale outMariaDB plc
ClustrixDB, now part of MariaDB, is a fully distributed and transactional RDBMS for applications with the highest scalability requirements. In this session Robbie Mihalyi, VP of Engineering for ClustrixDB, provides an introduction to ClustrixDB, followed by an in-depth technical overview of its architecture, with a focus on distributed storage, transactions and query processing – and its unique approach to index partitioning.
Getting started in the cloud for developersMariaDB plc
Looking to get up and running in the cloud, and start building applications with MariaDB as fast as possible? In this session, Thomas Boyd walks through the quick-start process of deploying MariaDB in the most popular public clouds. He then touches on some of the essential differences between cloud database services, helping you to create the cloud database strategy that best meets your needs.
How to power microservices with MariaDBMariaDB plc
Adoption of microservices is continuing at a rapid pace, but many deployments struggle when it comes to the database topology and data modeling. This session covers the pros and cons of different approaches (e.g., giving every microservice its own database or its own schema on a shared database) and various strategies for providing a consolidated view of data when different data is managed by different microservices.
Deploying MariaDB databases with containers at Nokia NetworksMariaDB plc
Nokia is focused on providing software and products that facilitate rapid development, deployment and scaling of products and services to customers. The Common Software Foundation (CSF) within Nokia develops and supports product reuse by multiple applications within Nokia, including MariaDB. Their focus over the last year has been to develop a containerized MariaDB solution supporting multiple architectures, including both clustering and primary/secondary replication with MariaDB MaxScale. In this talk, Rick Lane discusses this journey of these containerized solutions from development to customer trials, including problems encountered and solutions.
CCV: migrating our payment processing system to MariaDBMariaDB plc
CCV is a Dutch payment processor and loyalty provider. CCV's current payment processing platform is built on top of Microsoft SQL Server, but they are currently in the process of migrating it to MariaDB. This migration project is in progress and first production transactions are expected to run in 2020. In this session, Ernst Wernicke and Harry Dijkstra of CCV share how they are using MariaDB to meet critical high availability requirements, including geographic replication, zero data-loss, zero downtime (both planned and unplanned) and no single point of failure anywhere.
The role of databases in modern application developmentMariaDB plc
The rise of serverless microservices, event-driven application architecture and full-stack development with JavaScript and the MEAN stack is changing what application developers need from databases – and how they interact with them. In this session, MariaDB's Thomas Boyd discusses recent advancements in application development and architecture and explains how MariaDB supports them.
Global Data Replication with Galera for Ansell Guardian®MariaDB plc
Ansell Guardian® faced challenges with their previous database replication solution as their data and usage grew globally. They evaluated MariaDB/Galera and implemented it to replace their legacy solution. The implementation was smooth using automation scripts. MariaDB/Galera provided increased performance, faster deployment times, and more reliable data synchronization across their 3 data centers compared to their previous solution. It helped resolve a critical data divergence issue and improved the user experience. They plan to further enhance their database infrastructure using MaxScale in the future.
How THINQ runs both transactions and analytics at scaleMariaDB plc
THINQ provides a cloud-based Communications-Platform-as-a-Service (CPaaS) that routes tens of millions of phone calls per day for customers in enterprise and telecommunications industries. In this session Sasha Vaniachine, Senior Database Administrator at THINQ, explains how he combined MariaDB Server and MariaDB ColumnStore to support both high-performance transaction processing and scalable analytics. In addition, he shares some of THINQ's best practices and lessons learned from supporting an ever-increasing database workload that currently exceeds 10,000 transactions per second.
Caveats of hosting MariaDB on Microsoft Azure CloudMariaDB plc
Cloud service providers do not provide the same level of flexibility compared as an on-premises database. In this session, discover how Gaming Innovation Group (GiG) and MariaDB deployed a highly available setup on Microsoft Azure using the following technologies: Azure Load Balancer, CoroSync, Pacemaker, MariaDB MaxScale, MariaDB Cluster and MariaDB Server.
In 2018's user conference keynote MariaDB CEO, Michael Howard, announced an initiative to build a MariaDB DBaaS platform. In this session, the DBaaS team shares how MariaDB is approaching DBaaS, then discusses the role of containers and Kubernetes, the need for infrastructure-agnostic provisioning, support for day-two operations and enterprise requirements for large-scale DBaaS deployments.
Designing Resilient Application Platforms with Apache Cassandra - Hayato Shim...jaxLondonConference
Presented at JAX London 2013
All too often I have observed infrastructure designs for deploying Java applications come as an afterthought by businesses, technical analysts, and application developers. Choices of technologies are frequently made with no final deployment infrastructures being discussed. The talk will cover the design considerations on building resilient applications, and application deployment platforms across multiple data centres, and how organisations can leverage technologies such as Apache Cassandra to achieve this.
InnoDB Scalability improvements in MySQL 8.0Mydbops
This document provides an overview of new InnoDB scalability improvements in MySQL 8.0, including improved read and write scalability. It discusses how the InnoDB architecture was updated to support read/write workloads on modern hardware more efficiently. The redo log was redesigned to be lock-less. Contention aware transaction scheduling and other new features like instant alter algorithms and temporary session tablespaces were added to enhance performance.
Scylla Summit 2016: Why Kenshoo is about to displace Cassandra with ScyllaScyllaDB
Kenshoo is a leader in digital marketing with very heavy data usage. Learn about their big data challenges, the tools that they use, and their experience evaluating Scylla.
How to Secure Your Scylla Deployment: Authorization, Encryption, LDAP Authent...ScyllaDB
Scylla includes multiple features that collectively provide a robust security model. Most recently we announced support for encryption-at-rest in Scylla Enterprise. This enables you to lock-down your data even in multi-tenant and hybrid deployments of Scylla. Join Tzach and Dejan for an overview of security in Scylla and to see how you can approach it holistically using the array of Scylla capabilities. He will review Scylla Security features, from basic to more advanced, including:
Reducing your attack surface
Authorization & Authentication
Role-Based Access Control
Encryption at Transit
Encryption at Rest, in 2019.1.1 and beyond
LDAP authentication is a common requirement for any enterprise software. It gives users consistent login procedures across multiple components of the IT infrastructure, while centralizing the control of access rights. Scylla Enterprise now supports authentication via LDAP. We will look into how to configure Scylla Enterprise for LDAP interaction and how to fine-tune access control through it.
The document discusses MySQL 5.6 replication features including:
- Multi-threaded replication which allows parallel application of transactions to different databases for increased slave throughput.
- Binary log group commit which increases master performance by committing multiple transactions as a group to the binary log.
- Optimized row-based replication which reduces binary log size and network bandwidth by only replicating changed row elements.
- Global transaction identifiers which simplify tracking replication across clusters and identifying the most up-to-date slave for failover.
- Crash-safe slaves which store replication metadata in tables, allowing automatic recovery of slaves and binary logs after failures.
The document provides an introduction to MySQL. It discusses the history and founders of MySQL, an overview of MySQL products, and what MySQL is. MySQL is defined as a relational database management system that is open source, fast, reliable, and easy to use. It can be used as a standalone database or as part of web applications like LAMP stacks. The document also demonstrates MySQL Workbench and how to get involved with the MySQL community. It provides next steps for learning more about MySQL development and certification opportunities.
MySQL Cluster is a database that provides in-memory real-time performance, web scalability, and 99.999% availability. It uses memory optimized tables with durability and can handle high volumes of both reads and writes simultaneously in a distributed, auto-sharding fashion while maintaining ACID compliance. It offers high availability through a shared nothing architecture with no single point of failure and self-healing capabilities.
MySQL 8.0 is the latest Generally Available version of MySQL. This session will give a brief introduction to MySQL 8.0 and help you upgrade from older versions, understand what utilities are available to make the process smoother and also understand what you need to bear in mind with the new version and considerations for possible behaviour changes and solutions. It really is a simple process.
Ted Wennmark provides an overview of MySQL 8.0 and the upgrade process from previous versions. Key points include performance and scalability improvements in MySQL 8.0, new features like common table expressions and roles, and a shift to a continuous delivery release model. It is recommended to upgrade directly from 5.7 to 8.0 by moving through each minor release, and to use MySQL Shell's upgrade checker tool to identify any potential issues.
OSMC 2023 | What’s new with Grafana Labs’s Open Source Observability stack by...NETWAYS
Open source is at the heart of what we do at Grafana Labs and there is so much happening! The intent of this talk to update everyone on the latest development when it comes to Grafana, Pyroscope, Faro, Loki, Mimir, Tempo and more. Everyone has had at least heard about Grafana but maybe some of the other projects mentioned above are new to you? Welcome to this talk 😉 Beside the update what is new we will also quickly introduce them during this talk.
According to service scale, there are hundreds or thousands of running containers in your service. Should we monitor each container by microscope or monitor each microservice by magnifier? This depends which granularity can help us find and solve the problems. In this sharing, I will introduce how to use cAdvisor, Icinga2, InfluxDB and Grafana to build a self-hosted monitoring system. In addition, I also discuss with how to embrace open source and share some practical experiences.
Oracle Database 19c provides numerous new features and enhancements including:
- Improved performance for high volume inserts through a memory optimized mechanism.
- A new automatic indexing feature that implements indexes based on what a skilled performance engineer would do.
- Enhancements to sharding, Active Data Guard DML redirection, and hybrid partitioned tables that allow data to reside in both database segments and external files.
* Use cases of MySQL as well as edge cases of MySQL topologies using real-life examples and "war" stories
* How scalability and proxy wars make MySQL topologies more robust to serve webscale shops
* Open-source tools, utilities, and surrounding MySQL Ecosystem.
The document discusses MySQL Enterprise Monitor, an application that monitors MySQL database performance. It provides an overview of the product's architecture and features, how to install and configure it, and the benefits it provides, such as real-time performance monitoring, identifying problematic queries through query analysis, and advising on issues. It also notes how the tool helps improve performance, scalability, agility, productivity and reduce costs and risks for MySQL databases.
MariaDB SkySQL is a cloud database service that provides autonomous scaling, observability, and cloud backup capabilities. It offers multi-cloud and hybrid operations across AWS, Google Cloud, and on-premises databases. The service includes features like the Remote Observability Service (ROS) for monitoring across environments, and a Cloud Backup Service. It aims to provide a simple yet advanced service for scaling databases from small to extreme sizes with tools for automation, self-service, and unified operations.
Spring Cloud and Netflix OSS Overview is a technical document that:
1) Provides an overview of the Spring Cloud framework for building distributed and microservice applications, highlighting projects such as Spring Cloud Config, Spring Cloud Netflix, Spring Cloud Bus, Spring Cloud Stream and Spring Cloud Sleuth.
2) Describes the Netflix OSS projects integrated with Spring Cloud including service discovery with Eureka, client side load balancing with Ribbon, circuit breaking with Hystrix, routing and filtering with Zuul, and monitoring with Hystrix Dashboard and Turbine.
3) Includes demos of key Spring Cloud features like externalized configuration with Spring Cloud Config and propagating configuration changes with Spring Cloud Bus.
MariaDB is an open-source relational database management system that was created to be more open and community-focused than its predecessor, MySQL. It was founded in 2009 by the original developers of MySQL after Oracle acquired Sun Microsystems. MariaDB aims to preserve the open nature of MySQL by using an open governance model and keeping its code open source under GPL. It has become the default database in several major Linux distributions and is available on major cloud platforms. MariaDB provides an enterprise-grade database with high availability, performance, scalability and security features.
What's New in Apache Spark 2.3 & Why Should You CareDatabricks
The Apache Spark 2.3 release marks a big step forward in speed, unification, and API support.
This talk will quickly walk through what’s new and how you can benefit from the upcoming improvements:
* Continuous Processing in Structured Streaming.
* PySpark support for vectorization, giving Python developers the ability to run native Python code fast.
* Native Kubernetes support, marrying the best of container orchestration and distributed data processing.
Microservices @ Work - A Practice Report of Developing MicroservicesQAware GmbH
Cloud Native Night October 2016, Mainz: Talk by Simon Bäumler (Technical Chief Designer at QAware).
Join our Meetup: www.meetup.com/cloud-native-night
Abstract: This talk takes a practice oriented approach to examine microservice oriented architecture. It will show two real systems, one build from scratch in a microservice architecture, the other migrated from a monolithic system to a microservice architecture.
With the example of these two systems the pittfalls, advantages and lessons learned using microservice oriented architectures will be discussed.
While both systems use the java stack, including spring boot and spring cloud many topics will be kept general and will be of interest for all developers.
End-to-End, Source to Analytics, Data Lineage with Syncsort DMX-hPrecisely
Come see what new improvements we’ve made in Syncsort DMX-h, DataFunnel™ and DMX Change Data Capture.
Lineage is one thing that has been on the minds of a lot of our customers. This webinar will showcase new capabilities that allow deep tracking of field changes, transformations, merges and movement of data. Syncsort starts capturing lineage information at the moment of access with source systems, tracks all changes made, and data sources merged outside the cluster, and changes made on cluster. See how Syncsort helps you track your data’s changes from end to end, from source to analytics.
Confoo.ca conference talk February 24th 2021 on MySQL new features found in version 8.0 including server and supporting utility updates for those who may have missed some really neat new features
This document summarizes MariaDB 10.0 and what's new in the project. It provides an overview of MariaDB's history and goals of being compatible with MySQL. Key features of MariaDB 10.0 include backported features from MySQL 5.6, new features like multi-source replication, and engines for Cassandra and LevelDB. The roadmap is to have parity with MySQL 5.6 by MariaDB 10.1 while continuing to enhance and expand the feature set. Community involvement and the new MariaDB Foundation are discussed.
MariaDB Paris Workshop 2023 - NewpharmaMariaDB plc
This document summarizes Newpharma's transition from a standalone database server to an enterprise MariaDB Galera cluster configuration between 2018-2023. It discusses the business needs that drove the change, including increased traffic and access to multiple data sources. Key benefits of the Galera cluster are highlighted like synchronous replication, read/write access from any node, and automatic node joining. Challenges of migrating like converting table types and splitting large transactions are also outlined. The transition has supported Newpharma's growth to over 100 million euro in turnover.
MariaDB Paris Workshop 2023 - Performance OptimizationMariaDB plc
MariaDB is an open-source database that is highly tunable and modular. It allows for various storage engines, plugins, and configurations to optimize performance depending on usage. Key aspects that impact performance include memory allocation, disk access, query optimization, and architecture choices like replication, sharding, or using ColumnStore for analytics. Solutions like MyRocks, Spider, MaxScale can improve performance for transactional or large scale workloads by optimizing resources, adding high availability, and distributing load.
MariaDB Paris Workshop 2023 - MaxScale MariaDB plc
The document outlines requirements and criteria for a database solution involving two buildings 30km apart with a WAN link. The chosen solution was MariaDB with Galera cluster for high availability and synchronous replication across sites, along with Maxscale for read/write splitting and failover. Maxscale instances on each site allow for zero downtime database patching and upgrades per site, while the Galera cluster provides structure-independent synchronous replication between sites.
MariaDB Tech und Business Update Hamburg 2023 - MariaDB Enterprise Server MariaDB plc
MariaDB Enterprise Server 10.6 includes the following key features:
- New JSON functions and data types like UUID and INET4.
- Improved Oracle compatibility with function parameters.
- Enhanced partitioning capabilities like converting partitions.
- Optimistic ALTER TABLE for replicas to reduce downtime.
- Online schema changes without locking tables for improved performance.
- Security enhancements including password policies and privilege changes.
The document discusses high availability solutions for MariaDB databases. It begins by defining high availability and concepts like Recovery Time Objective (RTO) and Recovery Point Objective (RPO). It then presents different MariaDB and MaxScale architectures that provide high availability, including single node, primary-replica, Galera cluster, and SkySQL solutions. Key aspects covered are automatic failover, load balancing, data filtering, and service level agreements.
Die Neuheiten in MariaDB Enterprise ServerMariaDB plc
This document summarizes new features in MariaDB Enterprise Server. Key points include:
- MariaDB Enterprise Server is geared toward enterprise customers and focuses on stability, robustness, and predictability.
- It has a longer release cycle than Community Server, with new versions every 2 years and long maintenance cycles. New features from Community Server are backported.
- Recent additions include analytics functions, JSON support, bi-temporal modeling, schema changes, database compatibility features, and security enhancements.
- The upcoming 23.x release will include new JSON functions, data types like UUID and INET4, Oracle compatibility features, partitioning improvements, and Galera enhancements.
Beyond the basics: advanced SQL with MariaDBMariaDB plc
We've been writing SQL queries with WHERE, GROUP BY, ORDER BY, HAVING for decades, but we’re not using DOS 3.2 or Windows 1.0 anymore. Why limit yourself to SQL:86? In the past couple of releases, MariaDB has added support for features in the SQL:99 (common table expressions), SQL:2003 (window functions), SQL:2011 (system-versioned tables), and SQL:2016 (JSON) specifications – allowing you to build more complex data models (e.g., semi-structured or hierarchical) and write simpler, faster queries. In this session, Sergei Golubchik brings everyone up to speed on the latest SQL syntax supported in MariaDB.
Inside CynosDB: MariaDB optimized for the cloud at TencentMariaDB plc
Qinglin Zhang, Database Kernel Engineer at Tencent, introduces CynosDB, Tencent's self-developed database for the cloud. CynosDB is based on MariaDB Server, but separates computing and storage. Zhang goes on to provide a detailed explanation of the architecture with a focus on how Tencent implemented the computing and storage layers, and created Tencent’s MariaDB-based “Aurora”.
Migrating from InnoDB and HBase to MyRocks at FacebookMariaDB plc
Migrating large databases at Facebook from InnoDB to MyRocks and HBase to MyRocks resulted in significant space savings of 2-4x and improved write performance by up to 10x. Various techniques were used for the migrations such as creating new MyRocks instances without downtime, loading data efficiently, testing on shadow instances, and promoting MyRocks instances as masters. Ongoing work involves optimizations like direct I/O, dictionary compression, parallel compaction, and dynamic configuration changes to further improve performance and efficiency.
Configuring workload-based storage and topologiesMariaDB plc
This document discusses configuring workload-based storage and topologies in MariaDB. It introduces several MariaDB storage engines including InnoDB, MyRocks, Aria, Spider, and ColumnStore. For each engine, it provides an overview of use cases, key configuration parameters, and recommendations on when to use each engine. It also provides an example of using different engines like MyRocks, InnoDB and Spider across multiple microservices databases based on the workload. The document aims to help users choose the right storage engine for their specific workload needs.
Annex K RBF's The World Game pdf documentSteven McGee
Signals & Telemetry Annex K for RBF's The World Game / Trade Federations / USPTO 13/573,002 Heart Beacon Cycle Time - Space Time Chain meters, metrics, standards. Adaptive Procedural template framework structured data derived from DoD / NATO's system of systems engineering tech framework
Overview of Statistical software such as ODK, surveyCTO,and CSPro
2. Software installation(for computer, and tablet or mobile devices)
3. Create a data entry application
4. Create the data dictionary
5. Create the data entry forms
6. Enter data
7. Add Edits to the Data Entry Application
8. CAPI questions and texts
Combined supervised and unsupervised neural networks for pulse shape discrimi...Samuel Jackson
Our methodology for pulse shape discrimination is split into two steps. Firstly, we learn a model to discriminate between pulses using "clean" low-rate examples by removing pile-up & saturated events. In addition to traditional tail sum discrimination, we investigate three different choices for discrimination between γ-pulses, fast, thermal neutrons. We consider clustering the pulses directly using Gaussian Mixture Modelling (GMM), using variational autoencoders to learn a representation of the pulses and then clustering the learned representation (VAE+GMM) and using density ratio estimation to discriminate between a mixed (γ + neutron) and pure (γ only) sources using a multi-layer perceptron (MLP) as a supervised learning problem.
Secondly, we aim to classify and recover pile-up events in the < 150 ns regime by training a single unified multi-label MLP. To frame the problem as a multi-label supervised learning method, we first simulate pile-up events with known components. Then, using the simulated data and combining it with single event data, we train a final multi-label MLP to output a binary code indicating both how many and which type of events are present within an event window.
Solution Manual for First Course in Abstract Algebra A, 8th Edition by John B...rightmanforbloodline
Solution Manual for First Course in Abstract Algebra A, 8th Edition by John B. Fraleigh, Verified Chapters 1 - 56,.pdf
Solution Manual for First Course in Abstract Algebra A, 8th Edition by John B. Fraleigh, Verified Chapters 1 - 56,.pdf
Introduction to Data Science
1.1 What is Data Science, importance of data science,
1.2 Big data and data Science, the current Scenario,
1.3 Industry Perspective Types of Data: Structured vs. Unstructured Data,
1.4 Quantitative vs. Categorical Data,
1.5 Big Data vs. Little Data, Data science process
1.6 Role of Data Scientist
Harnessing Wild and Untamed (Publicly Available) Data for the Cost efficient ...weiwchu
We recently discovered that models trained with large-scale speech datasets sourced from the web could achieve superior accuracy and potentially lower cost than traditionally human-labeled or simulated speech datasets. We developed a customizable AI-driven data labeling system. It infers word-level transcriptions with confidence scores, enabling supervised ASR training. It also robustly generates phone-level timestamps even in the presence of transcription or recognition errors, facilitating the training of TTS models. Moreover, It automatically assigns labels such as scenario, accent, language, and topic tags to the data, enabling the selection of task-specific data for training a model tailored to that particular task. We assessed the effectiveness of the datasets by fine-tuning open-source large speech models such as Whisper and SeamlessM4T and analyzing the resulting metrics. In addition to openly-available data, our data handling system can also be tailored to provide reliable labels for proprietary data from certain vertical domains. This customization enables supervised training of domain-specific models without the need for human labelers, eliminating data breach risks and significantly reducing data labeling cost.
Getting Started with Interactive Brokers API and Python.pdfRiya Sen
In the fast-paced world of finance, automation is key to staying ahead of the curve. Traders and investors are increasingly turning to programming languages like Python to streamline their strategies and enhance their decision-making processes. In this blog post, we will delve into the integration of Python with Interactive Brokers, one of the leading brokerage platforms, and explore how this dynamic duo can revolutionize your trading experience.
3. SKYSQL - ULTIMATE MARIADB CLOUD
1. SkySQL is the first and only database-as-a-service (DBaaS) to bring the full power of
MariaDB Platform to the cloud.
2. Combining powerful enterprise features, MariaDB expertise and world-class support.
3. Whether it’s a single development database or thousands of production databases.
4. Secure by default.
5. Works out of the box.
6. Includes SkySQL Monitoring
SKYSQL MONITORING
3
5. For more SkySQL
SKYSQL MONITORING
5
Introducing the ultimate MariaDB
cloud, SkySQL
Shane Johnson, Senior Director of Product
Marketing, MariaDB
Watch the recording
7. SKYSQL MONITORING
… is the observability and monitoring service SkySQL providers
to the customers.
SKYSQL MONITORING
7
8. SKYSQL MONITORING
Database services are vital component of your applications.
Tracking of the availability and the database performance is key to your
business operations.
We understand that. We added SkySQL Monitoring as observability tool to
our SkySQL product.
It provides single pane of glass for monitoring your database services.
SKYSQL MONITORING
8
9. LIVE MONITORING
1. Provides real time database statistics for the DB Administrators and
Application Developers
2. Allows focusing on a specific component or specific measure.
3. Detection of problems introduced by external factors.
SKYSQL MONITORING
9
10. LIVE MONITORING
1. Provides real time database statistics for the DB Administrators and
Application Developers
2. Allows focusing on a specific component or specific measure.
3. Detection of problems introduced by external factors.
SKYSQL MONITORING
10
11. RETROSPECTIVE MONITORING
1. Historical trends of all metrics.
2. Comparison between two separate periods in time.
3. Comparison between two separate services.
4. Comparison between two separate version of the application,
database or database configuration.
SKYSQL MONITORING
11
12. UNDER THE HOOD
1. SkySQL Monitoring utilizes the same monitoring infrastructure used by our own
support teams.
2. It is built on top of the already proven and supported Prometheus and Grafana
products.
3. Extensible. Allows addition of new features.
SKYSQL MONITORING
12
13. PROMETHEUS
SKYSQL MONITORING
1. Open Source monitoring and alerting platform.
2. Widely supported and has very active community.
3. Supports Kubernetes and auto discovery of pods.
4. Flexible dimensional query language.
5. Pull based monitoring agents.
6. Supports Prometheus Alert Manager to handle alerts.
13
14. GRAFANA
SKYSQL MONITORING
1. Open Source system for observability and analysis.
2. Great for presenting and analysing time series and especially metrics data
3. Widely supported, very active community.
4. Highly customisable dashboards and chart panels.
5. Pluggable architecture, allows development of visualisation plugins.
6. Works great wit Prometheus & PromQL.
14
17. MONITORING AGENTS
MariaDB Prometheus Exporter
Collects the monitoring data from all MariaDB Products.
It is designed and optimised specifically for the MariaDB components used in
SkySQL
● MariaDB Enterprise Server
● MariaDB MaxScale
● MariaDB ColumnStore
● MariaDB Platform
MariaDB Prometheus Exporter is supported by MariaDB and updated with the new
features as soon as they are developed in our database products.
SKYSQL MONITORING
17
18. MONITORING AGENTS
Kubernetes Exporters (kube-state-metrics)
Export relevant pod metrics from the kubernetes infrastructure.
● Pod statuses
● Pod system metrics
Container Exporter (cAdvisor)
Export relevant system metrics from the containers.
● Container system metrics
SKYSQL MONITORING
18
19. MONITORING INFRASTRUCTURE
● Collects, stores and optimizes collected database metrics.
● Starts collecting metrics as soon as the database is created.
● Stores the stats optimized for further use.
● Ensures monitoring data is collected only once with minimal
impact on the database performance.
● Serves the metrics data as often as needed for the monitoring
dashboards
SKYSQL MONITORING
19
20. MONITORING DASHBOARDS
● Present all database service performance statistics as a glance.
● Focus on a database service or deep dive to a specific server.
● Fullscreen (NOC) View to monitor live mission critical
applications.
● Modern Web Application which supports all modern browsers on
pc and most tablets.
SKYSQL MONITORING
20
22. OPEN SKYSQL MONITOR
1. Create at least one database service in SkySQL
2. Add your IP to the SkySQL Monitoring whitelist.
This allows you to control the IP access to your monitoring.
You can change the whitelist any time.
3. You can open SkySQL Monitor for the first time, pressing the
“Dashboard” button from the “Monitoring” menu.
SKYSQL MONITORING
22
26. DASHBOARDS SCREEN
WHAT’S NEW IN MARIADB 3.0
26
Service Name
Topology Type
And server Info
Server
Dashboards
Time Filter
NOC View
Dashboard Tabs
Metric Charts
27. SERVICE OVERVIEW DASHBOARDS
Status Tab
Set of dashboards vital for the
whole database service.
Charts
● Current SQL Commands
● QPS
● CPU Load
● Used Connections
● Aborted Connections
● Replication Status
SKYSQL MONITORING
27
28. SERVICE OVERVIEW DASHBOARDS
Database Tab
Displays information about the database
as historical charts.
Charts
● MaxScale Service Connections
● MaxScale Server Connections
● Aborted Connections
● Table Locks
● Open Tables
● Tables Opened
SKYSQL MONITORING
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29. SERVICE OVERVIEW DASHBOARDS
Queries Tab
Displays information about queries as
historical charts.
Charts
● Top Commands (Recent/Hourly)
● Queries per Second
● Questions per Second
SKYSQL MONITORING
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30. SERVICE OVERVIEW DASHBOARDS
Replication Lags
Displays replication lags in historical
charts.
Charts
● GTID Replication Lag
● Seconds behind primary
● Questions per Second
SKYSQL MONITORING
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31. SERVICE OVERVIEW DASHBOARDS
System Tab
Displays system metrics in historical
charts.
Charts
● Top Commands (Recent/Hourly)
● Queries per Second
● Questions per Second
SKYSQL MONITORING
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32. SERVER DASHBOARDS
Status Tab
Presents current server overview.
Charts
● SQL Commands Mix
● Queries per Second
● Current CPU, RAM, Buffer Pools
● Database and Network
throughput.
SKYSQL MONITORING
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33. SERVER DASHBOARDS
Caches Tab
Displays historical charts about the
caches.
Charts
● Thread Cache
● Table Open Cache
● Table Definition Cache
● Query Cache and Activity.
SKYSQL MONITORING
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34. SERVER DASHBOARDS
Database Tab
Displays historical charts about MariaDB
database parameters.
Charts
● MariaDB Active Connections
● MariaDB Aborted Connections
● Thread Activity
● Temporary Objects Created
● Table Locs
● Open Tables
● Open Files
SKYSQL MONITORING
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35. SERVER DASHBOARDS
Queries Tab
Displays historical charts about MariaDB
running queries.
Charts
● Top commands by type
● Select and Sorts by Type
● Handler and Transactions
● Queries
● Slow Queries
SKYSQL MONITORING
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36. SERVER DASHBOARDS
Queries Tab
Displays historical charts for the system
metrics.
Charts
● Memory distribution and overview
● CPU
● InnoDB MB/sec
● I/O and IOPS
● Networks
SKYSQL MONITORING
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38. FOR EVERY DATABASE SERVICE
SKYSQL MONITORING
38
1. Available for all SkySQL customers.
2. Works out of the box
3. Based on recommendations from our MariaDB Remote DBAs.
4. Monitor all characteristic metrics for all standard SkySQL
database services.
Foundation Monitoring
39. EVERY DATABASE IS UNIQUE
SKYSQL MONITORING
39
Power Monitoring - Custom
1. Extends foundation tier.
2. Tailored monitoring solution to match the customer tailored power tier
service.
3. Supports custom topologies that might not be available for SkySQL
foundation tier.
4. Can support Alerts and Notifications.