Skip to main content

Web app comparison of async and real-time

Advantages of asynchronous web apps

  • Generic request/response structure
  • Stateless session control
  • Message queue management
  • Token access based on serverside date-time format
  • PostgreSQL paging using token-centric tables and functions
  • Shared pools of resources per customer
  • One-to-many security policies
  • Single domain name with TLS cert over HTTPS
  • Shared bandwidth for uploads/downloads
  • No endpoint/device registration
  • No direct access to server resources
  • Web app aggregation as control panel
  • A/B Testing

Advantages of (near) real-time web apps

  • Stateful session control
  • On-demand communication protocols per customer
  • Custom request/response structure per customer
  • Custom date-time formats per customer
  • Endpoint/device registration
  • PostgreSQL paging using static tables and aggregate functions
  • Immediate execution of requests
  • Dedicated pools of resources per customer
  • Dedicated TLS cert over HTTPS per customer
  • Dedicated IP address for SSH/RPC per customer
  • Dedicated bandwidth for uploads/downloads
  • One-to-one security policies
  • Managed services per customer
  • Direct access to server resources
  • Self-hosted control panel

Do you have a suggestion about how to improve this blog? Let's talk about it. Contact me at David.Brenner.Jr@Gmail.com or 720-584-5229.

Comments

Popular posts from this blog

Application behavior monitoring in Linux with Python

You can monitor application behaviors by collecting relevant machine data from your endpoint. You can use the machine data to investigate suspicious activity and create your own analysis. Before you start your investigation you will need to determine normal activity on your endpoint. Normal activity is the scope of functionality of the software on your endpoint during periods of low activity and high activity. You will need some kind of software that periodically collects specific machine data from your endpoint like my software developed in Python that's available for free download at https://github.com/davidbrennerjr/server-stats-collector Ingest one or more of the following machine data from Category #1. Ingest one or more of the following machine data from Category #2. Category #1 General system-wide error messages from /var/log/syslog Auditing logs of application rulesets Auditing logs of security contexts Auditing logs of

Network traffic monitoring in Linux with Python

You can investigate suspicious activity in your network traffic by collecting relevant machine data from your endpoint. You can use the machine data to create your own analysis. Before you start your investigation you will need to determine normal activity on your endpoint. Normal activity is the scope of functionality of the software on your endpoint during periods of low activity and high activity. You will need some kind of software that periodically collects specific machine data from your endpoint like my software developed in Python that's available for free download at https://github.com/davidbrennerjr/server-stats-collector Ingest one or more of the following machine data: Application specific logs from /var/log Raw dumps from sniffing at Layers 2-3 Raw dumps from /proc of kernel data structures Raw dumps of kernel routing tables General system-wide error messages from /var/log/syslog Do you

Continuous Integration (CI) Best Practices

Continuous Integration (CI) automates the building and testing of software in a test environment whenever a change is committed to a revision control system. CI performs QA testing of a change before adding it to the current working version. CI makes sure all development can be integrated into a build. CI Best Practices 1. Maintain a test environment that's a clone of the production environment. 2. Maintain a revision control system such as CVS, SVN or Git. 3. Automate the building of software and the documenting of code in the test environment. 4. Automate QA testing of a change then report that change to developers. 5. Commit changes regularly to avoid integration conflicts. 6. Monitor the revision control system for a commit then build the software before replacing the current working version. Do you have a suggestion about how to improve this blog? Let's talk about it. Contact me at David.Brenner.Jr@Gmail.com or 720-584-5229.