Omdia Universe: Selecting an Aiops Solution, 2021–22
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Reseller Approved Manufacturer(S)
Reseller Approved Manufacturer(s) 1Plus1 Technology EMC 5X Technology Red Hat, SAP 6D Global Adobe Accelera Solutions AppSense, EMC, HP, Imprivata, Liquidware Labs, Nutanix, Precise Biometrics, Red Hat, ServiceNow, Tintri, Vmware Adaptive Cyber RSA Adapture F5 Aderas, Inc. Delphix Advanced Computer Concepts Adobe, Condusiv, Gigamon, Nimble, RSA, SafeNet, Symantec, Veritas Advanced Market Place HP, Symantec Advanced Network Management F5, Splunk, VMware Advantaged Solutions SAP Affigent, LLC (Formerly TKCIS) Adobe, Axway, QTS, Salesforce.com, SAP Agilet Solutions Symantec Agosto Google Aikya Incorporated Salesforce.com AITS (Advanced IT Services, LLC) Symantec Akira Technologies Adobe Alamo City Engineering Services, Inc Adobe, AvePoint, Avue, HP, IBM, Imperva, Oblong, Precise Biometrics, Socrata, Tripwire Alchemy Technology Group AppSense Alexander Open Systems (AOS) F5 Alliance Technology Group Symantec Allied Network Solutions Adobe, SAP Alpha Sum Business Machines Adobe, Symantec, Veritas Alpha Technologies Tintri AlphaSix Corp (Synnex) Adobe, Arista, Nutanix, Splunk, Qlik Alvarez & Associates Adobe Amerinet of Michigan F5 AnaVation, LLC Salesforce.com Angus-Hamer, Inc. Adobe Apollo (Group) Information Systems Arista, FireEye Applied Engineering Management Carahsoft CON-SKUs Corp/Vizuri Aprisa Technology Adobe, EMC, RSA, Symantec, Veritas, Vmware Aquila HP, FireEye ARH, LLC EMC, F5, Symantec Assurance Data Imperva Atrion Nimble ATSolutions Inc Nimble August Schell ALL Aurora Adobe, Jama, Symantec Aurotech Veritas Avid Systems Good Technology/Blackberry, Precise Biometrics, RSA B7 ALL BAI Federal / Blackwood Associates Inc FireEye, Gigamon, Infoblox, Splunk BCS Systems Kofax Bear Bridge Symantec, Veritas Bear Data F5 Bell Techlogix Symantec, Vmware BizTech Fusion Box Black Box Network Services Certipath Blue Door Networks Splunk Blue Tech Adobe, Jama, SafeNet, Symantec Bluesource Inc Symantec Buchanan & Edwards EMC, F5, SAP Cambridge Computer Services Nimble Carolina Advanced Digital Infoblox Cask, LLC. -
State of 2017
STATE OF MODERN APPLICATIONS IN THE CLOUD 2017 Introduction — The Rise of Modern Applications What is the Modern Application? Today’s leading enterprises are striving to deliver high performance, highly scalable and always-on digital services. These services are built on custom “modern architectures” – an application stack with new tiers, new technologies, microservices and typically running on cloud platforms like Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform, etc. What does this report provide? The goal of this report is to provide data-driven insights, best practices and trends by analyzing technology adoption among Sumo Logic customers who run massive mission-critical modern applications on cloud platforms like AWS, Azure, and Google Cloud. Who should read this report? Cloud architects, Operations, DevOps and Security leaders and practitioners should leverage the learnings from this report to build, operate and secure modern applications effectively. Data Methodology and Assumptions • This data is derived from 1500+ Sumo Logic customers running applications on cloud platforms like AWS, Azure, Google Cloud, etc. All customer specific data is anonymized. • Customers use Sumo Logic to manage production applications and underlying infrastructure. Hence, this report provides a snapshot of the production application state. • The Sumo Logic analytics service runs on AWS. The experience and expertise of running this mission critical and massive service is also leveraged in this report. This report assumes that an app or -
Understanding Log Analytics at Scale O'reilly Report | Pure Storage
C om p lim e nt s of SECOND EDITION Understanding Log Analytics at Scale Log Data, Analytics & Management Matt Gillespie & Charles Givre REPORT SECOND EDITION Understanding Log Analytics at Scale Log Data, Analytics, and Management Matt Gillespie and Charles Givre Beijing Boston Farnham Sebastopol Tokyo Understanding Log Analytics at Scale by Matt Gillespie and Charles Givre Copyright © 2021 O’Reilly Media, Inc.. All rights reserved. Printed in the United States of America. Published by O’Reilly Media, Inc., 1005 Gravenstein Highway North, Sebastopol, CA 95472. O’Reilly books may be purchased for educational, business, or sales promotional use. Online editions are also available for most titles (http://oreilly.com). For more infor‐ mation, contact our corporate/institutional sales department: 800-998-9938 or [email protected]. Acquisitions Editor: Jessica Haberman Proofreader: Abby Wheeler Development Editor: Michele Cronin Interior Designer: David Futato Production Editor: Beth Kelly Cover Designer: Randy Comer Copyeditor: nSight, Inc. Illustrator: Kate Dullea May 2021: Second Edition February 2020: First Edition Revision History for the Second Edition 2021-05-05: First Release The O’Reilly logo is a registered trademark of O’Reilly Media, Inc. Understanding Log Analytics at Scale, the cover image, and related trade dress are trademarks of O’Reilly Media, Inc. The views expressed in this work are those of the authors, and do not represent the publisher’s views. While the publisher and the authors have used good faith efforts to ensure that the information and instructions contained in this work are accurate, the publisher and the authors disclaim all responsibility for errors or omissions, including without limitation responsibility for damages resulting from the use of or reliance on this work. -
Gigaom Radar for Cloud Observability V1.0
MARKET RADAR GigaOm Radar for Cloud Observability v1.0 ANDY THURAI | FEB 26, 2021 - 10:57 AM CST TOPIC: CLOUD INFRASTRUCTURE CREDIT: BAGOTAJ GigaOm Radar for Cloud Observability TABLE OF CONTENTS 1 Summary 2 Market Categories and Deployment Types 3 Key Criteria Comparison 4 GigaOm Radar 5 Vendor Insights 6 Analyst’s Take 7 About Andy Thurai 8 About GigaOm 9 Copyright GigaOm Radar for Cloud Observability v1.0 2 1. Summary Observability is an emerging set of practices, platforms, and tools that goes beyond monitoring to provide insight into the internal state of systems by analyzing external outputs. It’s a concept that has its roots in 19th century control theory concepts and is rapidly gaining traction today. Of course, monitoring has been a core function of IT for decades, but old approaches have become inadequate for a variety of reasons—cloud deployments, agile development methodology, continuous deployments, and new DevOps practices among them. These have changed the way systems, infrastructure, and applications need to be observed so events and incidents can be acted upon quickly. At the heart of the observability concept is a very basic premise: quickly learn what happens within your IT to avoid extended outages. And in the unfortunate event of an outage, you need to ensure that you can get to the root cause of it fast. Outages are measured by Mean Time To Resolution (MTTR) and it is the goal of the observability concept to drive the MTTR value to as close to zero as possible. No surprise, building resilient service delivery systems that are available with high uptime is the ultimate end goal for any business. -
Salesforce Shield
Salesforce Shield Enhance protection, monitoring, and retention of critical Salesforce data Overview The State of Cloud Security Companies of all sizes and industries are using Salesforce across departments to run their businesses faster. As adoption of Salesforce for critical business capabilities grows, monitoring Security and user behavior, tracking changes to data, and preventing data privacy concerns loss is more important than ever. With more sensitive data in are the top the cloud, security and compliance requirements also become inhibitors IT organizations face increasingly complex. Salesforce Shield helps address these when trying to integrate requirements while allowing you to proactively monitor user data for a shared single activity and enforce security policies. view of customers.* Salesforce Shield provides enhanced protection, monitoring, and retention of your critical data stored in Salesforce. Improving security policies and practices is the top • Native Encryption: Natively encrypt your most sensitive data priority for IT teams while retaining critical app functionality including search, over the next 12 to 18 workflow, and validation rules. months.* • Detailed Data & Monitoring: Gain access to detailed performance, security, and usage data for your Salesforce 65% apps in order to monitor critical business data, understand of IT leaders plan on user adoption across your apps, and troubleshoot and increasing data stored in optimize custom application performance. the cloud over the next 12 - 18 months.* • Security Policies: Build flexible, customizable security policies that give IT the power to identify and prevent malicious activity in real time. Retain data history for forensic * Salesforce State of IT level compliance as well as greater operational insights into Report, 2017 your business. -
Splunk Case Study: Familysearch
CASE STUDY FamilySearch Moves to Continuous Delivery and Gains Real-Time Visibility for AWS Migration Industry • Online services • Nonprofit Executive summary Splunk Use Cases • Application delivery Founded over 100 years ago, FamilySearch International is the largest • DevOps genealogy organization in the world, hosting, maintaining and sharing • Cloud solution genealogical records at FamilySearch.org and through over 4,600 fam- • IT operations management ily history centers in 132 countries. FamilySearch needed a way to move • Log management to a continuous delivery model, manage its all-in migration to Amazon Web Services (AWS) and immediately troubleshoot website errors. • Security Since beginning its effort, the organization has seen benefits including: Challenges • Wanted to increase update release frequency • Successful migration from monthly releases to over 900 deploys per day • Needed to monitor and immediately detect • Ability to re-allocate 12 developers to more value-added tasks changes to website to move to a DevOps • Visibility into the AWS environment to support AWS migration strategy model • Issues with troubleshooting and keeping website stable Why Splunk Business Impact FamilySearch planned to move to a continuous delivery model on • Successful migration from monthly releases AWS to increase business agility and more rapidly deliver features to 900 deploys per day to its patrons. To do so, the company needed a monitoring service • Enabled developers to easily see whether or that could immediately detect changes across its website properties not components were healthy following the push of a new release. This service needed to support • Moved to a DevOps model and achieved continuous delivery the cultural change to a DevOps deployment model. -
Application Data Analytics for Modern Applications How Sumo Logic’S Unified Machine Data Platform Changes the Management Game
Application Data Analytics for Modern Applications How Sumo Logic’s Unified Machine Data Platform Changes the Management Game An ENTERPRISE MANAGEMENT ASSOCIATES® (EMA™) White Paper Prepared for Sumo Logic July 2016 IT & DATA MANAGEMENT RESEARCH, INDUSTRY ANALYSIS & CONSULTING Application Data Analytics for Modern Applications: How Sumo Logic’s Unified Machine Data Platform Changes the Management Game Table of Contents Overview ................................................................................................................................................. 1 Telemetry, Big Operational Data, and the Real-Time Business ................................................................ 2 Modern Application Environments Require a New Approach to Application Management ................... 4 Sumo Logic: Cloud-Native Unified Logs and Metrics ............................................................................. 6 EMA Perspective ...................................................................................................................................... 8 ©2016 Enterprise Management Associates, Inc. All Rights Reserved. | www.enterprisemanagement.com Application Data Analytics for Modern Applications: How Sumo Logic’s Unified Machine Data Platform Changes the Management Game Overview telemetry – an automated communications process by which measurements and other data are collected at remote or inaccessible points and are subsequently transmitted to receiving equipment for monitoring1 The word “telemetry” has traditionally -
GCP Cloud Foundations #Whoami
GCP Cloud Foundations #whoami Federico Fregosi Current: Principal Consultant - Technical Past: [email protected] https://www.linkedin.com/in/federico-fregosi/ About Contino Contino is a leading transformation consultancy that helps large, heavily-regulated enterprises to become fast, agile and competitive. 360+ 5 300+ 150+ People Global offices Engagements Customers The deepest pool of We can scale rapidly More DevOps Specializing in helping the DevOps, data & cloud to support diverse transformation executed world's leading brands transformation talent client requirements than any other professional accelerate digital in the industry across the globe services firm transformation 3 Agenda 01 | Cloud Foundations 02 | Organization Structure & Resource Deployment 03 | Authentication & Authorization 04 | Networking 05 | Secrets Management 06 | Logging 07 | Operating Model 08 | FinOps - Billing 09 | Q&A 4 Why Do You Need Cloud Foundations? Landing zones enable management of standardised GCP projects, which in turn control your Virtual Private Clouds (VPCs) and consumption of GCP cloud services. ● Prevents Project Sprawl: Project provision can be managed as cloud engagement increases ● Minimises Engineering Overhead: Eliminating manual changes reduces complexity and enables scalability and consistency ● Enables Scaling by Design: Management of services and infrastructure in public cloud is made simple by the use of a well-designed landing zone ● Accelerates Consumption of Cloud Services: Allows for GCP projects to be provisioned with a -
FN1206: the Path to Operational Enlightenment
Use this if there will be two speakers for your session. FN1206: © 2019 SPLUNK INC. The Path to Operational Enlightenment An Introduction to Wire Data Simon O’Brien Vinu Alazath Principal Sales Engineer | Splunk Software Engineer | Splunk © 2019 SPLUNK INC. During the course of this presentation, we may make forward‐looking statements Forward- regarding future events or plans of the company. We caution you that such statements reflect our current expectations and estimates based on factors currently known to us Looking and that actual events or results may differ materially. The forward-looking statements made in the this presentation are being made as of the time and date of its live Statements presentation. If reviewed after its live presentation, it may not contain current or accurate information. We do not assume any obligation to update any forward‐looking statements made herein. In addition, any information about our roadmap outlines our general product direction and is subject to change at any time without notice. It is for informational purposes only, and shall not be incorporated into any contract or other commitment. Splunk undertakes no obligation either to develop the features or functionalities described or to include any such feature or functionality in a future release. Splunk, Splunk>, Turn Data Into Doing, The Engine for Machine Data, Splunk Cloud, Splunk Light and SPL are trademarks and registered trademarks of Splunk Inc. in the United States and other countries. All other brand names, product names, or trademarks belong to their respective owners. © 2019 Splunk Inc. All rights reserved. © 2019 SPLUNK INC. Agenda Challenges Product Overview Architecture and Deployment Demo Stream futures © 2019 SPLUNK INC. -
Designing Phelkstat: Big Data Analytics for System Event Logs
Designing PhelkStat: Big Data Analytics for System Event Logs Mohammed Salman∗, Brian Welch∗ and Joseph Tront∗ David Raymondy, Randy Marchanyy ∗Department of Electrical and Computer Engineering y IT Security Office Virginia Tech, Blacksburg Virginia Tech, Blacksburg Abstract—With wider adoption of micro-service based archi- tectures in cloud and distributed systems, logging and monitoring costs have become increasingly relevant topics of research. There are a large number of log analysis tools such as the ELK(ElasticSearch, Logstash and Kibana) stack, Apache Spark, Sumo Logic, and Loggly, among many others. These tools have been deployed to perform anomaly detection, diagnose threats, optimize performance, and troubleshoot systems. Due to the real- time and distributed nature of logging, there will always be a need to optimize the performance of these tools; this performance can be quantified in terms of compute, storage, and network utilization. As part of the Information Technology Security Lab at Virginia Tech, we have the unique ability to leverage production data from the university network for research and testing. We analyzed the workload variations from two production systems at Virginia Tech, finding that the maximum workload is about four times the average workload. Therefore, a static configuration can lead to an inefficient use of resources. To address this, we propose PhelkStat: a tool to evaluate the temporal and spatial attributes of system workloads, using clustering algorithms to categorize the current workload. Using PhelkStat, system parameters can be automatically tweaked based on the workload. This paper reviews publicly available system event log datasets from supercomputing clusters and presents a statistical analysis of these datasets. -
Leveraging Clustering and Natural Language Processing to Overcome Variety Issues in Log Management
Leveraging Clustering and Natural Language Processing to Overcome Variety Issues in Log Management Tobias Eljasik-Swoboda1 a, and Wilhelm Demuth2 1ONTEC AG, Ernst-Melchior-Gasse 24/DG, 1100 Vienna, Austria 2SCHOELLER NETWORK CONTROL GmbH, Ernst-Melchior-Gasse 24/DG, 1100 Vienna, Austria [email protected], [email protected] Keywords: Industrial Applications of AI, Intelligence and Cybersecurity, Machine Learning, Natural Language Processing, Trainer/Athlete Pattern, Log Analysis, Log Management, Event Normalization, Security Information and Event Management, Big Data Abstract: When introducing log management or Security Information and Event Management (SIEM) practices, organizations are frequently challenged by Gartner’s 3 Vs of Big Data: There is a large volume of data which is generated at a rapid velocity. These first two Vs can be effectively handled by current scale-out architectures. The third V is that of variety which affects log management efforts by the lack of a common mandatory format for log files. Essentially every component can log its events differently. The way it is logged can change with every software update. This paper describes the Log Analysis Machine Learner (LAMaLearner) system. It uses a blend of different Artificial Intelligence techniques to overcome variety issues and identify relevant events within log files. LAMaLearner is able to cluster events and generate human readable representations for all events within a cluster. A human being can annotate these clusters with specific labels. After these labels exist, LAMaLearner leverages machine learning based natural language processing techniques to label events even in changing log formats. Additionally, LAMaLearner is capable of identifying previously known named entities occurring anywhere within the logged event as well identifying frequently co-occurring variables in otherwise fixed log events. -
The New Normal: Cloud, Devops, and Saas
MARCH 2017 THE NEW NORMAL: CLOUD, DEVOPS, AND SAAS Methodology ANALYTICS TOOLS REIGN IN Sumo Logic commissioned UBM plc to conduct an online survey THE MODERN APP ERA in December 2016 exploring the As trends such as cloud computing and DevOps become the de facto current state of IT operations and modern application tools in standard, organizations are increasingly looking for next-generation enterprises. analytics tools and services that provide continuous intelligence to help them build, run, and secure modern applications, and to acceler- The final data set comprises 235 IT operations, application ate their journey to the cloud. However, they struggle with challenges development, and informa- related to security, siloed tools, and customization. A new survey con- tion security professionals. ducted by UBM and Sumo Logic highlights the need for visibility into All respondents are from companies with 500 or more and intelligence about the full IT application stack. employees, with roughly half from companies with 5,000 nterprise IT operates far diferently today than it did a decade or even or more employees. About just five years ago. The modern app era is redefining the way that one-third of respondents work in IT management, including enterprise IT teams build, run, manage, and secure their applications. titles such as CIO, CTO, VP of EInstead of running only their own servers in a traditional data center, IT, IT director and IT manager. today’s organizations are far more likely to be using public cloud computing Respondents’ companies are in a wide variety of industries, with services and/or their own private clouds.