Dynamic approach to applications discovery
Enterprise IT environments are complex and constantly changing with millions of inter-dependent components.
Any attempt to map and analyse enterprise applications that relies on manual labor will always be inaccurate due to
the potential for human error and the lag time between when the data is collected to when the analysis is done.
RejuvenApptor™ was designed to continuously map and analyze the topologies of the business applications/services:
- Auto-collect the data from servers, VMs, containers, clouds.
- Auto-identify the business applications/services, their topological structure/dependencies, data, unused assets, migration groups (to uncover even the forgotten and misinterpreted IT knowledge).
- Verify and augment this mapping with IT staff knowledge.
Example of an automatically-generated application diagram. All the decisions about what to show and what not are done by RejuvenApptor with no manual involvement.
Distinguishing features
| Feature | RejuvenApptor™ | Others |
|---|---|---|
| Automated business applications mapping and logical diagramming: | ||
| Software (applications) to server mapping. | Yes | Yes |
| Process-to-process or server-to-server connectivity diagramming. | Yes | Yes |
| Business application architecture and logical dependecies diagramming with minimal or no IT staff interviews. | Yes | No |
| Quality application topology models (accurate enough for non-trivial automated topological analysis): | ||
| Middleware objects level connections discovery (e.g., what database inside of an instance is used by an application). | Yes | Some |
| Ultra-deep software models (e.g., modeling Job schedulers at the individual Job dependencies level). | Yes | No |
| Deep software models (e.g., modeling individual databases and their tablespaces). | Yes | Some |
| Shallow software models that identify software installations, their version, vendor, and location. | Yes | Some |
| Generic software models (to identify custom and rare software out-of-the box). | Yes | No |
| 100% active software detection in a short time-frame (including custom software). | Yes | No |
| Classification of every dependency by type (e.g., IT infrastructure, NAS, etc.). | Yes | No |
| Automated application dependencies analysis algorithms for: | ||
| Identification of unused IT assets. | Yes | No |
| Migrations planning. | Yes | No |
| Client data classification (for security and BI). | Yes | No |
| Reliability and availability analysis. | Yes | No |
| Enterprise software licensing analysis. | Yes | No |
| Services-friendly fast and complete deployment that relies on the existing client tools and access policies. | Yes | No |
Fast data collection process
Fast rollout: our record is 7 days from the first client call to the report delivery time for a datacenter with 100s of servers.
100% Penetration: for most clients we cover even the servers off-the domain, behind firewalls, and otherwise hard to reach.
Our data collection flexibility results in the following advantages:
No network traffic is generated during most data collectins.
No new accounts are required.
No new firewall exceptions are required.
No middleware-specific accounts are required in most cases.
No network scanning is required.
Supported platforms
Servers:
Windows 2000 and later, Hyper-V, and same generations of Windows desktop OSs.
Linux (including zLinux) - all major distributions.
ESX/ESXi v3 and above (32 and 64 bit)
AIX v4 and above (POWER and Intel)
HP-UX v10 and above (PA-RISC and Intel)
Solaris v8 and above (SPARC and Intel)
FreeBSD v4 and above
Tru64 (OSF1)
OSX v10 and above
OpenVMS
Notable OS discovery features:
- OS support includes:
OS-specific file systems, mounted and shared file systems, Logical Volume Managers, HBA/SAN/NAS/iSCSI interfaces and their mapping to disks, devices,
CPU information (model, vendor, cores, threads, speed, virtual CPU pooling and pinning),
memory, swap,
processes, installed packages, bugfixes,
users, groups, AD roles, etc. - Correct discovery of CPU details on old systems (many CPUs report incorrect information about their cores/threads that most discovery tools happily incorrectly report it turn.)
- Utilization capturing over a period of time:
CPU (including I/O wait time on some OSs)
Memory and swap
I/O (interfaces and disks, volume and IOPs)
- Long-term connections monitoring: sounds trivial but most tools (especially agent-less) capture network connections at one point in time only.
The diagram below shows the typical percentage of application topological dependencies observed as a function of the monitoring time.
SAN, NAS, Networking devices:
There is experimental support for deep configuration and topology discovery on most popular NAS, SAN, and networking devices.
