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There are two concepts here – one is core product design, another is deployment optimization. Bloatware is traditionally used to mean OS and applications that grow fatter and more sluggish with each FCS. As part of bloatware deployment, optimization can be a useful tool for tailoring a product to the specific policies, traffic patterns, and risk posture of your organization and network topology. However, it is also often a crutch used to work around poor designs, finessing features and options into the optimal set of tradeoffs. Yet they are still tradeoffs -- something is lost.
Instead, we think you have the right to buy a product that works efficiently out of the box, without heavy optimization. If you have the time, budget, and desire to optimize, you can still choose to do so, but I prefer to see products that perform well at the default settings – with all the features you've invested in turned on.
Incorporating a Prevention Mindset into Threat Detection and ResponseThreat detection and response systems, by definition, are reactive because they have to wait for damage to be done before finding the attack. With a prevention-mindset, security teams can proactively anticipate the attacker's next move, rather than reacting to specific threats or trying to detect the latest techniques in real-time.
The report covers areas enterprises should focus on:
What positive response looks like.
Improving security hygiene.
Combining preventive actions with red team efforts.
Incident Readiness and Building Response Playbook
In this special report, learn the Xs and Os of any good security incident readiness and response playbook.
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User Rank: Ninja
10/31/2014 | 12:59:35 PM
Now, in terms of performance, it's a similar thing. You identify exactly what you need in your firewall, what you can replace with intermittant services rather than persistant, and also what can be replaced with pure staff power; re-design and roll out with only what you need; the understanding being that you do not turn anything off later without replacing it with another form of that service, or a modified version. But also, performance can be affected by the software itself - not all algorithms are equal and before buying deep analytics that are going to sit on your network, you should understand the code and whether there are better options out there; even bringing an in-house team to write the code so the footprint is small and the drag on performance is as minimal as possible may be worth the money in the long run.
Trim all the digital fat, and make sure only the best designed code is in place.
P.S. I suspect that of those admins interviewed, many of them didn't fully understand the options available in their software. Even bloatware can often be configurable to minimize features and for performance fine-tuning. Know your apps backward and forward, spend time with the application tech support to identify areas for improvement, and if that isn't working - buy another product.