Firewalls

There are two main reasons why some companies are hesitant to plug into the Internet.

  1. They know they’ll be exposing their company data to outside attacks from malicious individuals and malware.
  2. They fear their employees might get too many distractions: games, porn, chats, videos, and even social networking sites.

One vital component for your overall security strategy against such concerns? A firewall.

A firewall can block unauthorised access to certain Internet services from inside your organisation as well as prevent unauthenticated access from the outside. It is also used to monitor users’ activities while they were online.

In an enterprise setting, one may expect a collection of firewalls either for providing layered protection or segmenting off different units in the organisation. Some areas only need a standard line of defence while others require more restrictions. As such, certain firewalls may have different configurations compared to others.

Naturally, the more intricate an organisation’s defence requirements get, the more complex the task of monitoring, testing and configuring the firewalls becomes. That’s why we’re here to help.

  • We’ll evaluate your network as well as the security requirements of each department under your organisation to determine which firewall architecture is most suitable.
  • To achieve maximum efficiency, we’ll point out where each firewall should be positioned.
  • We’ll work with your key personnel to make sure all firewall configurations are set and optimised with your business rules in mind.
  • If a large number of firewalls are required, we’ll help you set up a firewall configuration management system.
  • Firewalls should be regularly tested and assessed to ensure they are in line with the organisation’s security policies. We’ll perform these routine tasks as well.

Firewalls aren’t very good at defending against sophisticated viruses. There are much better solutions for malware-related vulnerabilities, and we can help you in that regard too.

Other defences we’re capable of putting up include:

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Uncover hidden opportunities with energy data analytics

What springs to mind when you hear the words energy data analytics? To me, I feel like energy data analytics is not my thing. Energy data analytics, however, is of great importance to any organisation or business that wants to run more efficiently, reduce costs, and increase productivity. Energy efficiency is one of the best ways to accomplish these goals.

Energy efficiency is not about investment in expensive equipment and internal reorganization. Enormous energy saving opportunities is hidden in already existing energy data. Given that nowadays, energy data can be recorded from almost any device, a lot of data is captured regularly and therefore a lot of data is readily available.

Organisations can use this data to convert their buildings’ operations from being a cost centre to a revenue centre through reduction of energy-related spending which has a significant impact on the profitability of many businesses. All this is possible through analysis and interpretation of data to predict future events with greater accuracy. Energy data analytics therefore is about using very detailed data for further analysis, and is as a consequence, a crucial aspect of any data-driven energy management plan.

The application of Data and IT could drive significant cost savings in company-owned buildings and vehicle fleets. Virtual energy audits can be performed by combining energy meter data with other basic data about a building e.g. location, to analyse and identify potential energy savings opportunities. Investment in energy dashboards can further enable companies to have an ongoing look at where energy is being consumed in their buildings, and thus predict ways to reduce usage, not to mention that energy data analytics unlock savings opportunities and help companies to understand their everyday practices and operating requirements in a much more comprehensive manner.

Using energy data analytics can enable an organisation to: determine discrepancies between baseline and actual energy data; benchmark and compare previous performance with actual energy usage. Energy data analytics also help businesses and organisations determine whether or not their Building Management System (BMS) is operating efficiently and hitting the targeted energy usage goals. They can then use this data to investigate areas for improvement or energy efficient upgrades. When energy data analytics are closely monitored, companies tend to operate more efficiently and with better control over relevant BMS data.

Why Predictive Maintenance is More Profitable than Reactive Maintenance

Regular maintenance is needed to keep the equipment in your facility operating normally. All machinery has a design lifespan, and your goal is to extend this as long as possible, while maintaining optimal production levels. How you go about the maintenance matters, from routine checks to repairing the damaged component parts?all before the whole unit needs to be tossed away and a new one purchased and installed. Here, we will break down the different approaches used, and show you why more industries and businesses are turning to proactive maintenance modes as opposed to the traditional reactive approaches for their?field service operations.?

Reactive Maintenance: A wait and see game

Here, you basically wait for a problem to occur, then fix it. It’s also commonly referred to as a “Run-to-Failure” approach, where you operate the machines and systems until they break. Repairs are then carried out, restoring it to operational condition.?

At face value, it appears cost-effective, but the reality on the ground is far much different. Sure, when the equipment is new, you can expect minimal cases of maintenance. During this time, there?ll be money saved. However, as time progresses there?ll be increased wear, making reliance on a reactive maintenance approach a costly endeavour. The breakdowns are more frequent, and inconsistent as well. Unplanned expenses increase operational costs, and there will be lost productivity during the periods in which the affected machinery won’t be in operation.?

While reactive maintenance makes sense when you’re changing a faulty light bulb at home, things are more complicated when it comes to dealing with machinery in industries, or for those managing multiple residential and commercial properties. For the light bulb, it’s easier to replace it, and failure doesn’t have a ripple effect on the rest of the structures in the household. For industries, each time there is equipment failure, you end up with downtime, production can grind to a halt, and there will be increased environmental risks during equipment start-up and shutdown. If spare parts are not readily available, there will be logistical hurdles as you rush the shipping to get the component parts to the facility. Add this to overworked clients in a bit to complete the repair and to make up for lost hours and delayed customer orders.

For field service companies, more time ends up being spent. After all, there?s the need of knowing which parts needed to be attended to, where they are, and when the servicing is required. Even when you have a planned-out schedule, emergency repairs that are required will force you to immediately make changes. These ramps up the cots, affecting your operations and leading to higher bills for your client. These inconveniences have contributed to the increased reliance on?field service management platforms that leverage on data analytics and IoT to reduce the repair costs, optimise maintenance schedules, and?reduce unnecessary downtimes?for the clients.

Waiting for the machinery to break down actually shortens the lifespan of the unit, leading to more replacements being required. Since the machinery is expected to get damaged much sooner, you also need to have a large inventory of spare parts. What’s more, the damages that result will be likely to necessitate more extensive repairs that would have been needed if the machinery had not been run to failure.?

Pros of reactive maintenance

  1. Less staff required.
  2. Less time is spent on preparation.

Cons of reactive maintenance

  1. Increased downtime during machine failure.
  2. More overtime is taken up when conducting repairs.
  3. Increased expenses for purchasing and storing spare parts.?
  4. Frequent equipment replacement, driving up costs.?

This ?If it ain’t broke, don’t fix it? approach leads to hefty repair and replacement bills. A different maintenance strategy is required to minimise costs. Proactive models come into focus. Before we delve into predictive maintenance, let’s look at the preventive approach.?

Preventive Maintenance: Sticking to a timetable

Here, maintenance tasks are carried out on a planned routine?like how you change your vehicle?s engine oil after hitting a specific number of kilometres. These tasks are planned in intervals, based on specific triggers?like a period of time, or when certain thresholds are recorded by the meters. Lubrication, carrying out filter changes, and the like will result in the equipment operating more efficiently for a longer duration of time. While it doesn’t completely stop catastrophic failures from occurring, it does reduce the number of failures that occur. This translates to capital savings.??

The Middle Ground? Merits And Demerits Of Preventive Maintenance

This periodic checking is a step above the reactive maintenance, given that it increases the lifespan of the asset, and makes it more reliable. It also leads to a reduced downtime, thus positively affecting your company?s productivity. Usually, an 80/20 approach is adopted,?drawing from Pareto’s Principle. This means that by spending 80% of time and effort on planned and preventive maintenance, then reactive maintenance for those unexpected failures that pop up will only occur 20% of the time. Sure, it doesn’t always come to an exact 80/20 ratio, but it does help in directing the maintenance efforts of a company, and reducing the expenses that go into it.?

Note that there will need to be a significant investment?especially of time, in order to plan a preventive maintenance strategy, plus the preparation and delegation of tasks. However, the efforts are more cost effective than waiting for your systems and machinery to fail in order to conduct repairs. In fact, according to the US Dept. of Energy, a company can save between 12-18 % when using a preventive maintenance approach compared to reactive maintenance.

While it is better than the purely reactive approach, there are still drawbacks to this process. For instance, asset failure will still be likely to occur, and there will be the aspect of time and resource wastage when performing unneeded maintenance, especially when technicians have to travel to different sites out in the field. There is also the risk of incidental damage to machine components when the unneeded checks and repairs are being carried out, leading to extra costs being incurred.

We can now up the ante with predictive maintenance. Let’s look at what it has to offer:

Predictive Maintenance: See it before it happens

This builds on preventive maintenance, using data analytics to smooth the process, reduce wastage, and make it more cost effective. Here, the maintenance is conducted by relying on trends observed using data collected from the equipment in question, such as through vibration analysis, energy consumption, oil analysis and thermal imaging. This data is then taken through predictive algorithms that show trends and point out when the equipment will need maintenance. You get to see unhealthy trends like excessive vibration of the equipment, decreasing fuel efficiency, lubrication degradation, and their impact on your production capacities. Before the conditions breach the predetermined parameters of the equipment’s normal operating standards, the affected equipment is repaired or the damaged components replaced.??

Basically, maintenance is scheduled before operational or mechanical conditions demand it. Damage to equipment can be prevented by attending to the affected parts after observing a decrease in performance at the onset?instead of waiting for the damage to be extensive?which would have resulted in system failure. Using?data-driven?field service job management software will help you to automate your work and optimise schedules, informing you about possible future failures.

Sensors used record the condition of the equipment in real time. This information is then analysed, showing the current and future operational capabilities of the equipment. System degradation is detected quickly, and steps can be taken to rectify it before further deterioration occurs. This approach optimises operational efficiency. Firstly, it drastically reduces total equipment failure?coming close to eliminating it, extending the lifespan of the machinery and slashing replacement costs. You can have an orderly timetable for your maintenance sessions, and buy the equipment needed for the repairs. Speaking of which, this approach minimises inventory especially with regards to the spare parts, as you will be able to note the specific units needed beforehand and plan for them, instead of casting a wide net and stockpiling spare parts for repairs that may or may not be required. Repair tasks can be more accurately scheduled, minimising time wasted on unneeded maintenance.??

Preventive vs Predictive Maintenance?

How is predictive different from preventive maintenance? For starters, it bases the need for maintenance on the actual condition of the equipment, instead of a predetermined schedule. Take the oil-change on cars for instance. With the preventive model, the oil may be changed after every 5000?7500 km. Here, this change is necessitated because of the runtime. One doesn’t look at the performance capability and actual condition of the oil. It is simply changed because “it is now time to change it“. However, with the predictive maintenance approach, the car owner would ideally analyse the condition of the oil at regular intervals- looking at aspects like its lubrication properties. They would then determine if they can continue using the same oil, and extend the duration required before the next oil change, like by another 3000 kilometres. Perhaps due to the conditions in which the car had been driven, or environmental concerns, the oil may be required to be changed much sooner in order to protect the component parts with fresh new lubricant. In the long run, the car owner will make savings. The US Dept. of Energy report also shows that you get 8-12% more cost savings with the predictive approach compared to relying on preventive maintenance programs. Certainly, it is already far much more effective compared to the reactive model.?

Pros of Predictive Maintenance

  1. Increases the asset lifespan.
  2. Decreases equipment downtime.
  3. Decreases costs on spare parts and labour.
  4. Improves worker safety, which has the welcome benefit of increasing employee morale.
  5. Optimising the operation of the equipment used leads to energy savings.
  6. Increased plant reliability.

Cons of Predictive Maintenance

  1. Initial capital costs included in acquiring and setting up diagnostic equipment.
  2. Investment required in training the employees to effectively use the predictive maintenance technology adopted by the company.

The pros of this approach outweigh the cons.?Independent surveys on industrial average savings?after implementing a predictive maintenance program showed that firms eliminated asset breakdown by 70-75%, boosted production by 20-25%, and reduced maintenance costs by 25-30%. Its ROI was an average of 10 times, making it a worthy investment.

How DevOps oils the Value Chain

DevOps ? a clipped compound of development and operations – is a way of working whereby software developers are in a team with project beneficiaries. A client centred approach extends the project plan to include the life cycle of the product or service, for which the software is developed.

We can then no longer speak of a software project for say Joe?s Accounting App. The software has no intrinsic value of its own. It follows that the software engineers are building an accounting app product. This is a small, crucially important distinction, because they are no longer in a silo with different business interests.

To take the analogy further, the developers are no longer contractors possibly trying to stretch out the process. They are members of Joe?s accounting company, and they are just as keen to get to market fast as Joe is to start earning income. DevOps uses this synergy to achieve the overarching business goal.

A Brief Introduction to OpsDev

You can skip this section if you already read this article. If not then you need to know that DevOps is a culture, not a working method. The three ?members? are the software developers, the beneficiaries, and a quality control mechanism. The developers break their task into smaller chunks instead of releasing the code to quality control as a single batch. As a result, the review process happens contiguously along these simplified lines.

Code QC Test ? ? ?
? Code QC Test ? ?
? ? Code QC Test ?
? ? ? Code QC Test
Colour Key Developers Quality Control Beneficiary

This is a marked improvement over the previously cumbersome method below.

Write the Code ? Test the Code ? Use the Code
? Evaluate, Schedule for Next Review ?

Working quickly and releasing smaller amounts of code means the OpsDev team learns quickly from mistakes, and should come to product release ahead of any competitor using the older, more linear method. The shared method of working releases huge resources in terms of user experience and in-line QC practices. Instead of being in a silo working on its own, development finds it has a richer brief and more support from being ?on the same side of the organisation?.

The Key Role that Application Program Interfaces Play

Application Program Interfaces, or API?s for short, are building blocks for software applications. Using proprietary software-bridges speeds this process up. A good example would be the PayPal applications that we find on so many websites today. API?s are not just for commercial sites, and they can reduce costs and improve efficiency considerably.

The following diagram courtesy of TIBCO illustrates how second-party applications integrate with PayPal architecture via an API fa?ade.

Working quickly and releasing smaller amounts of code means the OpsDev team learns quickly from mistakes, and should come to product release ahead of any competitor using the older, more linear method. The shared method of working releases huge resources in terms of user experience and in-line QC practices. Instead of being in a silo working on its own, development finds it has a richer brief and more support from being ?on the same side of the organisation?.

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The DevOps Revolution Continues ?

We close with some important insights from an interview with Jim Stoneham. He was general manager of the Yahoo Communities business unit, at the time Flickr became a part. ?Flickr was a codebase,? Jim recalls, ?that evolved to operate at high scale over 7 years – and continuing to scale while adding and refining features was no small challenge. During this transition, it was a huge advantage that there was such an integrated dev and ops team?

The ?maturity model? as engineers refer to DevOps status currently, enables developers to learn faster, and deploy upgrades ahead of their competitors. This means the client reaches and exceeds break-even sooner. DevOps lubricates the value chain so companies add value to a product faster. One reason it worked so well with Flickr, was the immense trust between Dev and Ops, and that is a lesson we should learn.

?We transformed from a team of employees to a team of owners. When you move at that speed, and are looking at the numbers and the results daily, your investment level radically changes. This just can’t happen in teams that release quarterly, and it’s difficult even with monthly cycles.? (Jim Stoneham)

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