Big Data, Machine Learning Shape Performance
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IBM IT Service Management: Serve Your Clients, Not Your IT 2
IBM IT Service Management January 2016 IBM IT Service Management: Serve your clients, not your IT 2 Contents 3 What’s keeping you up at night? Optimize decisions with insights 4 Embrace agility to accelerate transformation Succeed and manage in a hybrid environment 5 IBM IT Service Management: Tool for your hybrid envrionment Operations Performance Automation Workload Automation Service Desk Analytics 9 Why choose IBM for your middleware solution? Solid Foundation of Trusted Technology 10 What IT Service Management solutions are right for you? What can you do next? IBM IT Service Management 3 What’s Keeping you up at night? Optimize decisions with insights Are you having trouble falling asleep or staying asleep—can Let’s investigate further why solutions that help you optimize you sleep at all? We know what’s keeping today’s CIO up decisions with insights are so critical to your company’s at night. success. Businesses all over the world run on applications and data. Ensuring the smooth running of business applications and the Your business does as well. The success of your business health of your infrastructure and network is vital, but without relies on your IT infrastructure and network because they the right tools, it is also difficult. The impact of outages can support and carry the applications that represent the lifeblood be costly, and their repercussions can have a direct impact on of your company. How to keep things up and running, revenue and profits, brand equity, and, most importantly, your connected, responsive, and relevant could be keeping you customers. up at night. -
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. -
Application Performance Management for Dummies®, Riverbed Special Edition Published by John Wiley & Sons, Inc
These materials are the copyright of John Wiley & Sons, Inc. and any dissemination, distribution, or unauthorized use is strictly prohibited. These materials are the copyright of John Wiley & Sons, Inc. and any dissemination, distribution, or unauthorized use is strictly prohibited. Application Performance Management Riverbed Special Edition by Lawrence C. Miller, CISSP These materials are the copyright of John Wiley & Sons, Inc. and any dissemination, distribution, or unauthorized use is strictly prohibited. Application Performance Management For Dummies®, Riverbed Special Edition Published by John Wiley & Sons, Inc. 111 River St. Hoboken, NJ 07030-5774 www.wiley.com Copyright © 2013 by John Wiley & Sons, Inc., Hoboken, New Jersey No part of this publication may be reproduced, stored in a retrieval system or trans- mitted in any form or by any means, electronic, mechanical, photocopying, record- ing, scanning or otherwise, except as permitted under Sections 107 or 108 of the 1976 United States Copyright Act, without the prior written permission of the Publisher. Requests to the Publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, (201) 748- 6011, fax (201) 748-6008, or online at http://www.wiley.com/go/permissions. Trademarks: Wiley, the Wiley logo, For Dummies, the Dummies Man logo, A Reference for the Rest of Us!, The Dummies Way, Dummies.com, Making Everything Easier, and related trade dress are trademarks or registered trademarks of John Wiley & Sons, Inc. and/or its affiliates in the United States and other countries, and may not be used without written permission. Riverbed, OPNET, Steelhead, Cascade, Wireshark, FlyScript, Stingray, and the Riverbed logo are trademarks or registered trademarks of Riverbed Technology Inc. -
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. -
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 -
The State of Analytics in IT Operations
White Paper IT Operations Management The State of Analytics in IT Operations IT operations analytics Introduction holds considerable promise for making day-to-day If you lived through the AI (artificial intelligence) hype of the 1990s or earlier, you might be skeptical about IT Ops work easier. seeing the term in such frequent use these days. AI can mean many different things, andalways has. It has also changed names a few times, from IT Operations Analytics (ITOA) to Algorithmic IT Ops, AIOps, and Cognitive Operations. But over the past two years, with influential analyst firms like Gartner and Forrester getting on board with the term, AI is getting more respect, and it’s getting more practical. According to a recent Forrester survey, ITOA is the number one application of AI technology that busi- nesses are considering. Also high on Forrester’s list are business insight and security, all of which are related to ITOA at a fundamental level. IT Ops Analytics all starts with data collection or monitoring data. Analytics is dependent on data and lots of it, often called Big Data. Data is the food that fuels analytics, without it analytics has nothing to look at to find patterns or anomalies that provide us insight. IT Operations Analytics holds considerable promise for making day-to-day IT Ops work easier. But what does this mean for IT Ops specialists who aren’t trained in analytics? Do they now need to take classes in data science and machine learning, and learn to write the algorithms that lie at the heart of analytics capabilities? No. -
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 -
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 Opsramp State of Aiops Report
The OpsRamp State of AIOps Report Report The OpsRamp State of AIOps Report The Signal in the Noise: The Truth on How AIOps is Truly Impacting Business Performance Page: 1 The OpsRamp State of AIOps Report Executive Summary It’s Time to Understand How AIOps Is Actually Being Used While classic event correlation and modern IT operations analytics tools have been around for some time, the AIOps market is fairly new, with Gartner coining the phrase back in 2016. Today, AIOps expectations are reaching peak levels of inflated expectations (see Google Trends to get a glimpse of its growth). Figure 1 - Google Trends Report for AIOps (April 2016 - April 2019) Page: 2 The OpsRamp State of AIOps Report To help you understand the true impact of AIOps, OpsRamp has assembled ‘The State of AIOps’ report which is probably one of the few surveys that is based on data from IT Methodology practitioners who are currently using machine learning-powered event analysis. We conducted the survey through a third The purpose of commissioning The State of AIOps report was three-fold: party with a total of 200 respondents. All • Understand which technology capabilities and use cases were most important for respondents worked at the IT manager AIOps tool acquisition level or above, across IT operations, • Quantify the operational benefits of AIOps for incident management DevOps or Site Reliability • Track leading concerns that might stall AIOps adoption in the future Engineering teams. Read the report to learn, from the trenches, what truly matters while selecting an AIOps Enterprises surveyed had more than solution for a modern enterprise. -
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.