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What are the steps to set up and configure APM for Events Service, when deploying Analytics on-prem?   Overview The Events Service should have its own Java Agent and Machine Agent. Step 1. How do I set up Machine Agents for Events Service nodes? Step 2. Set up Application Agents for the Events Service Step 3. Set Up an Application Agent for Elasticsearch Step 4. Begin Monitoring Troubleshooting Where do I view logs?  How do I troubleshoot common problems?    Step 1. How do I set up Machine Agents for Events Service Nodes? To monitor the hardware health of the Events Service nodes, this example uses a Machine Agent installation. For more details, see the AppDynamics Machine Agent installation documentation. Link each Machine Agent with either: the Events Service's API,  or the Events Service's Elasticsearch Java Agents   The unique host ID configuration option enables the linking.   Complete the following procedure: Decide whether you are linking the Machine Agent to the Events Service API or the Events Service Elasticsearch. Note the relevant uniqueHostId value that you configured in the vmoptions file.  For example:  - Dappdynamics.agent.uniqueHostId=EventsService01   Edit < machine-agent-home >\conf\controller-info.xml such that <unique-host-id>EventsService01</unique-host-id> corresponds to that value. Verify that the Java Agent and Machine Agent are associated by viewing the Applications > Tiers and Nodes tab in the Controller:   Step 2. Set up application Agents for the Events Service Common Application Agent Configurations Locate your Events Service and Java Agent directories. For this example, use the following: /opt/appdynamics/events-service = <Events-Service-Home> /opt/appdynamics/AppAgent = <AppAgent-Home> Collect Controller information by using the information in the following table: Item Example Data hostname <controller_host> port <controller_port> account name <account_name> access key <access_key> name of the APM application that monitors the Events Service EventsService   Edit the controller-info.xml file. Add your equivalent to <controller_host>, <controller_port> , <account_name> , <access_key> to AppAgent <AppAgent-Home>/conf/ or the relative directory to be <AppAgent-Home>/conf/controller-info.xml Edit the events-service.vmoptions file under <Events-Service-Home>/processor/config> Add -javaagent:<AppAgent-Home>/javaagent.jar in the events-service.vmoptions file Stop the event service. ./bin/events-service.sh stop Restart the event service to match the new configuration.  ./bin/events-service.sh start -p ./conf/events-service-api-store.properties &   Step 3. Set Up an Application Agent for Elasticsearch Add a security policy for AppAgent file to access from within the Elasticsearch process. Create the <Events-Service-Home>/conf/elasticsearch.policy file: grant codeBase "file:<AppAgent-Home>/-” { Permission java.security.AllPermission; };   Create and edit a new <Events-Service-Home>/conf/elasticsearch.vmoptions file. Copy the existing <Events-Service-Home>/conf/events-service.vmoptions file Enable a separate vmoptions file for Elasticsearch by editing the <Events-Service-Home>/conf/events-service-api-store.properties property as follows: ad.es.jvm.options.name =elasticsearch.vmoptions Append the following new properties to the new elasticsearch.vmoptions file . -javaagent:<AppAgent-Home>/javaagent.jar -Dappdynamics.socket.collection.bci.enable=true -Dappdynamics.agent.tierName=EventsService-Elasticsearch -Dappdynamics.agent.nodeName=Elasticsearch01 -Djava.security.policy=<Events-Service-Home>/conf/elasticsearch.policy   Specify a hard (not relative) path in -Djava.security.policy . Append the following new properties to events-service.vmoptions -javaagent:<AppAgent-Home>/javaagent.jar -Dappdynamics.socket.collection.bci.enable=true -Dappdynamics.agent.uniqueHostId=EventsService01 -Dappdynamics.agent.tierName=EventsService-API -Dappdynamics.agent.nodeName=API01   Step 4. Begin Monitoring Manually restart the single Events Service process that you are trying to instrument: bin/events-service.sh stop bin/events-service.sh start -p conf/events-service-api-store.properties & Through the Controller UI, verify that both Application Agents are reporting: To prevent termination after logoff of jobs, detach the job that you just started from the active terminal by using the disown command: #[1] bin/events-service.sh start -p conf/events-service-api-store.properties disown %1   Troubleshooting Where do I view logs? How do I troubleshoot common problems?   Where do I view logs? View the logs from their typical locations, shown in the following table:   Log Location API store <Events-Service-Home>/logs/events-service-api-store.log Elasticsearch <Events-Service-Home>/logs/appdynamics-events-service-cluster.log Java Application Agent <AppAgent-Home>/ver<Your App Agent Version>/logs/<Your agent.nodeName>/agent<Latest App Agent Start Time>.log   How do I troubleshoot common problems? Run troubleshooting commands when you encounter common problems. Problem  Command When Elasticsearch is starting, you see vm.max_map_count errors sudo sysctl -w vm.max_map_count=262144 If the system starts running out of descriptors, check /etc/security/limits.conf Substitute the name of the user running Elasticsearch for the asterisk ("*" ) echo "*"   soft nofile   65536" | sudo tee -a etc/security/limits.conf echo "*"   hard nofile   65536" | sudo tee -a etc/security/limits.conf   ... View more

Considerations for configuring rules to enforce Analytics trade-offs   Overview Create the configuration rules for your on-premise Controller based on your analytics resource priorities and strategic trade-offs.   Note: These configuration rules are described in the Browser RUM (BRUM) , Mobile RUM (MRUM), and IoT Monitoring documentation.    Analytics Trade-offs As you add new applications to your Analytics deployment, you can control resource consumption by making strategic trade-offs.    Understanding Analytics trade-offs begins with this concept:   Anytime we acquire or generate more information to analyze, that costs something. Conversely, by choosing not to acquire or generate unimportant information, we can realize savings.    To make a trade-off, you take an action that either increases or decreases the amount of information that Analytics must process. Ask yourself:   Does the potential benefit of the action justify the cost, for the user’s customer's particular situation?   Costs or savings can be in terms of: Licenses Hardware Energy use   The following table shows important trade-offs to consider: Action Benefit Cost When is the cost justified? Discover Ajax calls More information about activity in the browser Many more requests for the system to handle  When there is a web front-end that depends heavily on Ajax Restrict discovery to pages of a specific type of pages that satisfy particular rules Limit burden on the Events Service Less information about activity in the browser When knowing about the excluded information adds little value, and/or unnecessarily complicates your picture of application behavior Restrict Analytics BT Events Limit burden on the Events Service Less information about BTs   When knowing about the excluded information adds little value, and/or unnecessarily complicates your picture of application behavior Restrict Analytics log events Limit burden on the Events Service Less log information to search when troubleshooting When knowing about the excluded information adds little value, and/or unnecessarily complicates your picture of application behavior   For more details, see Configuring Application Analytics . ... View more

 Analytics' Recipe Book for on premises configuration   Overview The following tables contain data based on EUM Processor and Events Service load testing combinations under synthetic load. The tables have been normalized.    Once the EUM traffic profile has been estimated, you can use these maximum load measurement results to establish which T-shirt size the EUM Processor and Events Service should be.   How do I account for multiple traffic types? If you plan to consume more than one type of traffic, then you should add EUM loads using beacons, and add Events Service loads using Normalized Performance Events.   Normalized EUM Processor and Events Service Load Testing Tables Node Configuration and System Architecture Events Service T-shirt Sizes Shard Replication in Elasticsearch     Normalized EUM Processor and Events Service Load Testing Tables Use the following maximum load measurement results to establish the EUM Processor and Event Service T-shirt sizes. Web Mobile  IoT EUM Processor T-shirt Sizes Events Service T-shirt Sizes   Web Maximum Load Testing Results EUM Size Events Service Size EUM Beacons per Minute Max  Events Svc Browser Record Events/M inute Max  Events Svc Browser S ession Events/M inute Maximum Events Service Normalized Performance Events /  per Minute Small Small 60K 60K 3K 60k browser records/min * 0.33 Normalized Performance Events / browser record event 3k Browser session events/min * 5 Normalized Performance Events / session event= 35k Normalized Performance Events / min Medium Medium 120K 120K 6K 120k browser records/min * 0.33 Normalized Performance Events / browser record event 6k Browser session events/min * 5 Normalized Performance Events / session event = 70k Normalized Performance Events / min Large Large 300K 300K 12K + 300k browser records/min * 0.33 Normalized Performance Events / browser record event 12k Browser session events/min * 5 Normalized Performance Events / session event = 160k Normalized Performance Events / min   Mobile Maximum Load Testing Results EUM Size Events Service Size Max EUM Beacons /M inute Max Events Service Mobile Snapshot Events /M inute Max Events Service Mobile Session Events /M inute Maximum Events Service Normalized Performance Events /  per Minute Small Large 90K 70K 40K + 70k Mobile snapshots/min * 0.33 Normalized Performance Events / Mobile snapshot event 40k Mobile session events/min * 5 Normalized Performance Events / session event = 223.3k Normalized Performance Events / min Medium XLarge 130K 110K 61K 110k Mobile snapshots/min * 0.33 Normalized Performance Events / Mobile snapshot event 61k Mobile session events/min * 5 Normalized Performance Events / session event 341.7k Normalized Performance Events / min Large XXLarge 550K 1.35M 118K 3.5 Mobile snapshots/min * 0.33 Normalized Performance Events / Mobile snapshot event 118k Mobile session events/min * 5 Normalized Performance Events / session event = 1756.7k Normalized Performance Events / min   IoT Maximum Load Testing Results EUM size Events Service size Maximum EUM Beacons / Min Max. Events Service IoT Rcords / Minute Maximum Events Service Normalized Performance Events / Minute Small Medium 110K 500K 500k IoT records / min * 0.33 Normalized Performance Events / IoT record event 166.7k Normalized Performance Events/min Medium Large 300K 600K 600k IoT records / min * 0.33 Normalized Performance Events / IoT record event 200k Normalized Performance Events/min Large XLarge 600K 1M 1M IoT records / min * 0.33 Normalized Performance Events / IoT record event 333.3k Normalized Performance Events/min   EUM Processor T-shirt Sizes T-shirt Size EUM Recommended Instance Type EUM Processor JVM Heap Size Small 4 core, 16GB RAM, disk 300GB 600IOPS (m4.xlarge) 11GB Medium 8 core, 32GB RAM, disk 300GB 600IOPS (m4.2xlarge) 30GB Large 16 core, 64GB RAM, disk 300GB 600IOPS (m4.4xlarge) 50GB     Node Configuration and System Architecture The Events Service node network setup used in this example has speeds of >= 1 GBPs. Latencies are similar to a switched network, such that: Average SSD latencies are < 1.2ms per read/write operation Average nVME latencies are < 0.4ms per read/write operation   If SaaS deployment is not an option, consider splitting the deployment on the Application level into multiple accounts and multiple controllers.   AppDynamics strongly recommends using SSD-backed instances for Analytics—SAN is not recommended. This is because AppDynamics follows the official Elasticsearch hardware guidelines, configurations vary widely, and AppDynamics cannot guarantee that a particular SAN configuration is supported.   Finally, you should avoid network-attached storage (NAS). A NAS solution is often slower, displays larger latencies with a wider deviation in average latency, and is a single point of failure.     Events Service T-shirt Sizes The following table shows the recommended number of nodes and node configuration for each T-shirt size. See Stipulate throughput by license type in the Quick Method.   T-Shirt Size Number of Nodes Normalized Performance Events per Minute Recommended Node Configuration SaaS Recommended or Required? X-Small 1 50000 4 core, SSD (ideally as nVME) or HDD 7,200 RPM No Proof of Concept, Dev, & Demo Small 3 100000 4 core, SSD (ideally as nVME) (i2.xlarge) No Medium 3 195761 8 core, SSD (ideally as nVME) (i2.2xlarge) No Large 5 284000 8 core, SSD (ideally as nVME) (i3.2xlarge) Recommended sometimes XLarge 10 438000 8-16 core, nVME  (i3.2xlarge) Recommended XXLarge 20 600000 8-16 core, nVME (i3.2xlarge) Depending on query load and other factors that impact performance, larger nodes may be more suitable Required On premises deployments of this size are not supported Overall deployment should be structured as multiple smaller deployments, each with its own controller   Once you determine your T-shirt size, refer to the non-virtual hardware specifications that correspond to the relevant EC2 instance size: AWS EC2 i2 AWS EC2 i3 The Events Service should be on separate, dedicated server(s).     Shard Replication in Elasticsearch We assume a replication factor of 1 for Elasticsearch. Performance tests show that there is an upper limit to the average CPU performance of a cluster. Due to the replication and synchronization of Elasticsearch node segments, the limit decreases as the number of nodes increases.   Risks and Benefits Not enabling Elasticsearch replication has both risks and benefits: Risks The lack of redundancy highly increases the likelihood of data loss if any nodes in the Events Service cluster go down.   Benefits CPU ingestion utilization decreases by approximately 55% Data drive storage requirements decrease by approximately 50%   Data Replication Since Elasticsearch builds in redundancy with replicas, there is no need for RAID configurations other than RAID 0. For this reason, Elasticsearch recommends using RAID 0 and increasing write throughput.   If RAID (1,3,5) replication is selected, AppDynamics does not provide support for disk performance or data integrity issues. ... View more

When planning instrumentation for deploying Analytics on-prem, how do I build the traffic profile?   Table of Contents How do I understand my traffic for sizing? How do I consider EUM usage when building my Events Service traffic profile?   How do I understand my traffic for sizing? Understanding the characteristics of your traffic is the foundation for successful sizing. To build a traffic profile, answer the following questions.   If I have Business Transactions (BTs) in an APM application I want to enable Analytics on: Is it a new or an existing APM application? Do I have Log Analytics licenses? Additional estimate methods    Am I seeking to enable Analytics on an existing or new APM application? Existing APM application Identify the BTs you need to instrument from the APM application page. For each BT, count how many tiers, and on average how many requests are going through each tier for a single origin BT. Each tier for a single BT produces at least one event if a request passes through the tier and node. Identify the peak sum of BTs per minute for all BTs and sum the count of events per those BTs to estimate the peak events per min. This enables you to size for the number of nodes and CPU. New APM application For a more accurate option, instrument and then go through an existing application. If not instrumented, you should try to access using the available number of requests coming through each tier by: count of log lines/timestamps existing database aggregations Q/A with application stakeholders Figure 1 shows an example of how many BT events per tier are generated. Figure 2 shows the estimated number of events per APM BT.     A tier can be called multiple times by originating BT, thus producing multiple events. If the request performs asynchronous calls on a single node then it's possible that a single request on a single tier could output multiple segments (events). Each async thread call becomes its own segment in the Java Agent. In .NET, results from an async call could be merged into one or more segments (events).    Figure 1:  Example of how many BT events per tier are generated     Figure 2: Estimated number of events per APM BT     Do I have Log Analytics licenses? If so, then: Collect log samples for a period of time per source. Determine the start and end times of each log Determine the file sizes which determine the required disk size for the Events Service footprint (which is approximately = file size * 1.7) Determine the number of lines or timestamps. Each is counted as one event Calculate the average number of events per minute for each log source Avg number of lines per source number 1 = (file 1 num of lines / (end time file 1 - start time file 1) + … + (file N num of lines / (end time file N - start time file N )) / number of files in source number 1 Then, sum the averages for an overall average number of log events Logs     You can also use these additional estimation methods: What licenses do you have? The limits on traffic that licenses specify serve as useful benchmarks when you estimate events later in the Instrument, Run, and Refine process. What is the shape of traffic over time? Is your traffic consistent or spiky? What times of the day, week, month, season, or year produce changes? You should plan your deployment to perform well at peak loads, or at least at the 90th percentile loads. What are typical numbers for concurrent users? Does this vary over time, and if so, what are the patterns? What are typical patterns of user behavior? Are users doing the exact same thing repeatedly, or taking diverse actions? How are the patterns concentrated or spread out over time? Mobile app crash rate If any, what is the typical crash rate for your mobile apps?     How do I consider End User Management (EUM) usage when building my Events Service traffic profile?  Unlike Business Transaction (BT) or Log Analytics licenses, the number of EUM licenses does not translate into a good basis to estimate what size machine can support a particular deployment. EUM performance depends on the number of beacons.   To accurately estimate expected beacons, you must understand: The millions of browser page views and/or IOT events allowed by the licenses can be distributed in many ways over the year. Temporal distribution of traffic is key.  Mobile licenses, by contrast, allow some thousands of mobile agents to connect per month—but any of those agents can send an unlimited number of requests. User behavior is key.   When building the traffic profile, you need detailed and accurate information. The following will help you determine the projected EUM Analytics load:    Browser Request User Monitoring (BRUM) EUM license types and their unit-to-beacon relationships     Browser Request User Monitoring (BRUM) How many page views? How many beacons per page view? Typically, it is one.  Typically, each beacon would produce one session event and one browser request event. Mobile Request User Monitoring (MRUM) How many session events per user event? Typically, it is one.  How many MobileSnapshots per user event? Typically, it is one.  How many crashes in a worst-case scenario? Review the MobileCrashReport. Internet of Things (IoT) How many devices and device types? What is a typical transmission rate per minute per device type?   This table lists the unit-to-beacon relationship for each EUM license type. EUM License Type Units Unit-to-Beacon Relationship BRUM one million page views/year One to one IoT TBD million IOT events/year One to one MRUM 5K mobile agents/month can connect No unit-beacon relationship can be derived because: Each mobile agent can send unlimited requests per month. The total number of mobile beacons is not limited. EUM license types and their unit-to-beacon relationships   Note: For up-to-date licensing information for EUM Analytics, click here .   Note: By default, each EUM Analytics event type is limited to 50GB per day. You can adjust that limit inside each Events Service node’s properties located in this directory: <Events-Service-Home>/conf/events-service-api-store.properties  in the  ad.es.event.maxDailyEventTypeBytesQuota folder ... View more

Overview To deploy analytics successfully, you should understand the following concepts: EUM and Analytics Events How do Events Flow Through the System? Beacons Resource Timing Snapshots Performance Considerations Analytics Trade-offs   EUM and Analytics Events In the AppDynamics model, each major service produces its own types of events. That includes services not relevant here such as Application Monitoring, Database Visibility, and Server Visibility.    Note : Sizing analytics for database visibility is treated as a special case. If you have questions, contact your AppDynamics representative.   In this example, we'll look at End User Monitoring and Analytics services, and their respective events. Service Event Definition End User Monitoring Change in the state of a web, mobile, or IoT front-end Analytics Change in the state of: Business Transaction Application log Custom-defined event created for analytics purposes   Sometimes it makes sense to distinguish between EUM and Analytics events. However, in this discussion, we'll treat both types of events as Analytics events.    Event Categorization by Behavior Another way to categorize events is to consider how they behave in the system. This yields two broad categories of event types described in the following table: Event Category Event Type How the Event Behaves Examples Upsert, also known as Update Transaction Analytics, Browser Session, Mobile Session Freshly creates something that is modifiable, or modifies that thing; often events with multiple segments or components An Upsert could modify or create: Business Transaction (BT) which has multiple segments, each associated with a different tier Browser session which has multiple variables, such as one that is modified when the user clicks a radio button Publish Log, Snapshot, Crash Report, IoT, Custom API Creates immutable artifacts A Publish event could create a log entry   How the Events Service is provisioned in terms of hardware, OS tuning, and network tuning, determines the limits of Events Service's ability to handle incoming events, and the quality of its performance. Hardware includes cores (CPUs), memory, and disk storage.   How do Events flow through the system? What Flows into the Events Service from the EUM Server? What Flows into the Events Service from the Analytics Agent? Controller Queries   Events come to the Events Service in two flows: from the EUM Server from the Analytics Agent   The Events Service also handles queries from the Controller. Even though Controller queries are not events, but they still contribute to load on the Events Service.   What flows into the Events Service from the EUM Server? Demand on the EUM Server consists of the sum total of clicks and other actions that occur in browsers, or on mobile or IoT devices. We cannot limit that demand because we have no control over what flows into the EUM Server.   However, we do control what flows out of the EUM Server, and thus can limit the demand that the Events Service and other parts of the system must handle.   The process is:  AppDynamics agents in browsers, and on mobile and IoT devices, generate a snippet of data called a beacon for every click or other action. The agents send the beacons to the EUM Server. The EUM Server determines whether the beacons are valid, based on configurable rules. Based on beacon content, the EUM Server generates snapshots, session information, and metadata and then sends these to the Events Service.   Based on configurable rules, the EUM Server decides whether the event that the beacon represents should be discovered or not. Events that are not discovered are dropped from the system; the Events Service is never aware of them.   What flows into the Events Service from the Analytics Agent? The Analytics Agent Forwards Business Transaction events to the Events Service Generates Log events and sends them to the Events Service   Controller Queries The Controller persists metadata, which includes license and account information, and event schemas. It then synchronizes the metadata with the Events Service. This enables AppDynamics to process licensing rules and limits, honor expirations, and authenticate publish/query calls using the account name and access key. When the user creates Analytics queries in ADQL, the Controller sends them to the Events Service—these are Controller Queries.   Controller Queries also originate from EUM and DBMon dashboards and screens.   Beacons Beacons, Events, and Sessions Beacons from Browser Actions  Beacons from Mobile and IoT Actions   When an AppDynamics Agent, or SDK instrumented code, detects an action in the browser or on a mobile or IoT device, it sends a beacon (a JSON file which contains keys and values) to the EUM Server.   Beacons, Events, and Sessions A beacon is a network request from an EUM agent that includes an agent ID and metadata about the events or activities that were reported.   A session consists of a series of beacons that share the same agent ID and which occurred within a configured period of time. The default configured period is five minutes. A session ends and a new one is created if there was no activity during that configured period of time.    For example, if a series of beacons are sent within the default configured period of five minutes with no inactivity and have the same agent ID, the events reported in those beacons are included in the same session. If an event occurs outside of the configured period of inactivity, however, a new session is created.   Beacons from Browser Actions  The JavaScript Agent generates a beacon for every browser action. The EUM Server determines which page type the beacon represents. Page types are virtual page , base page , iFrame , and Ajax call .    According to the default page naming rules : Virtual and base pages and iFrames are discovered Ajax calls are not discovered, because they generate more requests than other page types When you want to constrain which pages to discover, work with page naming rules. For example, to direct the system to only discover pages from the host server1, you would write the rule hostname = servers.    For more details, see: Configure Page Identification and Naming for its description of virtual and base pages, and iFrames   Beacons from Mobile and IoT Actions The Mobile Agent generates a beacon for every action or event on a mobile device. The IoT Java Agent generates a beacon for every action on an IoT device.    Use the C/C++, Java SDK, or the REST API to specify the events to send.   For more details, see: Instrument Applications with the IoT Java SDK Instrument Applications with the IoT C/C++ SDK Instrument Applications with the IoT REST APIs The EUM Server inspects the beacons and applies rules based on the characteristics and content of the network requests.   Resource Timing Snapshots AppDynamics Agents collect load times for each resource on a web page and send the load times to the EUM Server. The EUM Server packages up a percentage of the page-load events as a Resource Timing Snapshot and sends that to Analytics. Analytics uses Resource Timing Snapshots to tell AppDynamics users which resources use the most time to load.   Performance considerations For browser traffic, t he more resources in a web page, the more CPU EUM processor uses. Upserts are more expensive on Events Service side.    Analytics Trade-offs As you add new applications to your Analytics deployment, you can control resource consumption by making strategic trade-offs.    Understanding Analytics trade-offs begins with the following concept: Anytime we acquire or generate more information to analyze, that costs something. Conversely, by choosing not to acquire or generate unimportant information, we can realize savings.    To make a trade-off, you take an action that either increases or decreases the amount of information that Analytics must process.   Ask yourself: Does the potential benefit of the action justify the cost, for the customer's particular situation?   Costs or savings can be in terms of: Licenses Hardware Energy use   The following table shows important trade-offs to consider: Action Benefit Cost When is the cost justified? Discover Ajax calls More information about activity in the browser Many more requests for the system to handle  When there is a web front-end that depends heavily on Ajax Restrict discovery to pages of a specific type or pages that satisfy particular rules Limit burden on the Events Service Less information about activity in the browser When knowing about the excluded information adds little value, and/or unnecessarily complicates your picture of application behavior Restrict Analytics BT events Limit burden on the Events Service Less information about BTs Restrict Analytics log events Limit burden on the Events Service Less log information to search when troubleshooting For more details, see Configuring Application Analytics . ... View more