Monthly Archives: March 2017

CNE’s Node.js Agent – Monitor Node.js Application

We are all familiar with the functionality of the Node.js Agent, but what we need to familiarize ourselves is with the insights of the production systems while developing Node.js applications. And to assist us here, CNE has introduced Node.js to their existing suite of tools.

Node.js plays the role of a Monitoring application. CNE understands how crucial Constant monitoring is to avoid slowing down of the product and even more to avert downtimes. This application also monitors the details of the inefficiencies of the databases, slow 3rd party APIs and web services.

CNE introduces Node.js as a Monitoring Solution

CNE is a high-end, suite of tools designed by administrators and performance experts to improve performance, scalability and stability of enterprise applications. The CNE Node.js Agent helps you monitor Node.js applications during the production phase. It can then be determined which applications are slower than normal or producing a lot of errors. It also provides tools for troubleshooting and monitoring the application problems.

Node.js CNE – Proven Monitoring Solution

  • Monitoring performance: Reviewing the most important performance metrics to ensure stability
  • Monitoring the Code:Reporting at a code level, thus, monitoring the execution of each function at the production level
  • Monitor Server status which includes recording of:
    • Sufficient disk space on server
    • Sufficient CPU time
    • Sufficient memory
    • Reliable Network Connection
    • Request and response details of the server
    • Generate server crash reports
  • Monitoring Database operations: Reviewing the time spent in the database including noSQL datastores like Redis, mongoDB, and memcached.
  • Monitor Network connections:Monitor network connections to reduce communication delays between services
  • Monitoring error rates: This can be achieved by Generating an Error report of http request calls

Node.js server Increases Performance since:

  • HTTP module Added:Identifies and designs theHTTP module for collecting the Http calls. Support is provided to the HTTPS feature in Applicare server and to the Node.js agent.
  • Reduction in Average Response times: Calculate the time taken to complete the request along with sql or no-sql calls.Collects and records the elapsed time for the SQL calls happening in Node.js application.
  • Distributable database:Instruments various SQL(mysql, oracledb) and No-SQL(mongodb) database modules,
  • Monitoring Web Transactions: The request module is used to Monitor/collect the external web service calls, executed by the Node application
  • ART Platform:Monitor/Calculate the ART and platform information of the server
  • Reduction in Error Rate: Monitor/collect the HTTP error data released in the Node.js application
  • Average Response Time:Calculate the elapsed time of the respective http call.
  • Generate Alerts: Receive alerts to errors generated by applications, and thus enabling prompt fixtures.
  • Throughput (requests per minute):js application status would be updated per minute (custom defined), to ensure the health of the application under monitoring.
  • Control flow Transactions: The Node.js Agent monitors applications dynamically when a program is running or being executed. The Node.js runtime metrics help in monitoring the health of the Node.js process.
  • Admin Console: Applicare admin console assists in configuration and implementation of the instrument and un-instruments
  • Business transaction Manager (BTM): This feature has been designed, where admin can add few specific http, sql and web service calls to the BTM list. Thus admin incorporates a few rules that consolidate the history of data and enhance the application or the server configuration.

CNE overcomes the Challenges by:

  • User Experience Manager(UEM): This functionality is used todesign and develop the script in to the response of Node.js application.
  • Protobuf technology: This technology is integrated for secure data sharing between CNE server and Node.js agent. This technology is also used to monitor the Collection and Execution time for sql calls
  • Low Expectancy: This principle is assists in identifying the respective Http calls and thus calculating the server time spent on the particular requests.

Business Benefits

  • Broader Market Insight:By adding one new technology agent to the current suite of  tools in the Applicare project, Arcturustech opened up to a wider range of clients looking for robust and latest technologies
  • Increased Clients:Also in a very short period of time Arcturustech found the increased requirement for the Node.js solution to clients who already had the server installed.
  • Visible Scalability:Development of a Connection between the high-end technologies based servers. Thus enabling the consolidation of data featuring it as a library in runtime environment.

IOT and Stream Analytics

IoT and Stream Analytics

-by CNE Systems

In an Internet of Things (IoT) environment, machines, sensors, and devices are connected to networks and data systems. These things or smart objects generate large volumes of fast moving data with huge potential for insight generation.

This generation requires an immediate decision. Every decision has a window of time when information is valuable. Thus assigning deadlines to these decisions and if information arrives too late, the opportunity to make the call based on analytical insights is lost.

This is where we introduce/incorporate Streaming Analytics. Stream Analytics makes it easy to set up real-time analytic computations on data streaming from devices, sensors, web sites, social media, applications, infrastructure systems, and more.

  • Streaming Analytics is the ability to constantly calculate statistical analytics while moving within the stream of data. Also Streaming Analytics allows management, monitoring, and real-time analytics of live streaming data.
  • Real-time data feeds enable users to analyze constantly churning information as it changes. Viewing events as they unfold accelerates action.
  • Decision makers can detect both threats and opportunities in fast moving data and act immediately.
  • Real-time integration lets analysts immediately compare new data to historical data to put current conditions in context.
  • Nobody has to wait for information to be compiled and decisions are not delayed by drawn out data processes.
  • Streaming Analytics involves knowing and acting upon events happening in your business at any given moment.
  • Streaming Analytics can help companies identify new business opportunities and revenue streams which results in an increase in profits, new customers, and improved customer service. A Streaming Analytics platform can process millions and tens of millions of events per second.
  • Since Streaming Analytics occurs immediately, companies must act on the analytics data quickly within a small window of opportunity before the data loses its value. We will focus on the data that originates from the Internet of Things (IoT)
  • Scenarios of real-time streaming analytics can be found across all industries: personalized, real-time stock-trading analysis and alerts offered by financial services companies; real-time fraud detection; data and identity protection services; reliable ingestion and analysis of data generated by sensors and actuators embedded in physical objects (Internet of Things, or IoT); web click stream analytics; and customer relationship management (CRM) applications issuing alerts when customer experience within a time frame is degraded.

Continue reading